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USGS2024

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

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

Enviornmental Monitoring and Assessment↗
USGS2025

Cancer risk and estimated lithium exposure in drinking groundwater in the US

Importance Lithium is a naturally occurring element in drinking water and is commonly used as a mood-stabilizing medication. Although clinical studies have reported associations between receiving lithium treatment and reduced cancer risk among patients with bipolar disorder, to our knowledge, the association between environmental lithium exposure and cancer risk has never been studied in the general population. Objectives To evaluate the association between exposure to lithium in drinking groundwater and cancer risk in the general population. Design, Setting, and Participants This cohort study included participants with electronic health record and residential address information but without cancer history at baseline from the All of Us Research Program between May 31, 2017, and June 30, 2022. Participants were followed up until February 15, 2023. Statistical analysis was performed from September 2023 through October 2024. Exposure Lithium concentration in groundwater, based on kriging interpolation of publicly available US Geological Survey data on lithium concentration for 4700 wells across the contiguous US between May 12, 1999, and November 6, 2018. Main Outcome and Measures The main outcome was cancer diagnosis or condition, obtained from electronic health records. Stratified Cox proportional hazards regression models were used to estimate the hazard ratios (HRs) and 95% CIs for risk of cancer overall and individual cancer types for increasing quintiles of the estimated lithium exposure in drinking groundwater, adjusting for socioeconomic, behavioral, and neighborhood-level variables. The analysis was further conducted in the western and eastern halves of the US and restricted to long-term residents living at their current address for at least 3 years. Results A total of 252 178 participants were included (median age, 52 years [IQR, 36-64 years]; 60.1% female). The median follow-up time was 3.6 years (IQR, 3.0-4.3 years), and 7573 incident cancer cases were identified. Higher estimated lithium exposure was consistently associated with reduced cancer risk. Compared with the first (lowest) quintile of lithium exposure, the HR for all cancers was 0.49 (95% CI, 0.31-0.78) for the fourth quintile and 0.29 (95% CI, 0.15-0.55) for the fifth quintile. These associations were found for all cancer types investigated in both females and males, among long-term residents, and in both western and eastern states. For example, for the fifth vs first quintile of lithium exposure for all cancers, the HR was 0.17 (95% CI, 0.07-0.42) in females and 0.13 (95% CI, 0.04-0.38) in males; for long-term residents, the HR was 0.32 (95% CI, 0.15-0.66) in females and 0.24 (95% CI, 0.11-0.52) in males; and the HR was 0.01 (95% CI, 0.00-0.09) in western states and 0.34 (95% CI, 0.21-0.57) in eastern states. Conclusions and Relevance In this cohort study of 252 178 participants, estimated lithium exposure in drinking groundwater was associated with reduced cancer risk. Given the sparse evidence and unknown mechanisms of this association, follow-up investigation is warranted.

contiguous United States↗
USGS2026

Special issue “The 2024 M7.6 Noto Peninsula earthquake and seismic swarm”

The 2024 Mw7.5 (M JMA 7.6) Noto Peninsula earthquake struck the Noto Peninsula, central Japan on January 1, 2024, causing widespread damage. This Mw7.5 mainshock, together with the prolonged seismic swarm that persisted in the northeastern Noto Peninsula since the end of 2020, of which the largest event was the 2023 M JMA 6.5 earthquake, constitutes one of the most significant seismic sequences in Japan in recent decades. The sequence provides a rare opportunity to investigate the complex interplay among swarm activity, fluid migration, fault geometry and distribution, and the preparatory conditions required for a large inland crustal earthquake. Motivated by this scientific context, this special issue brings together studies examining the sequence from diverse disciplinary perspectives, incorporating seismic, geodetic, and tsunami-related observations and modelling.

Noto Peninsula↗
USGS2025

Quantitative evaluations of earthquake early warning performance using “Did You Feel It?” and post-alert surveys

We examine responses to the U.S. Geological Survey’s “Did You Feel It?” (DYFI) survey and its companion earthquake early warning (EEW) questionnaire to assess the performance of the U.S. ShakeAlert EEW system directly from the alert recipients’ perspectives. ShakeAlert rapidly detects earthquakes and develops alert information, but as official alert delivery partners issue these alerts, it is thus difficult to determine how many people were alerted and when. We investigate DYFI reports for six California earthquakes that had EEW alerts and substantial responses to the DYFI EEW questionnaire. Comparisons of ShakeAlert predictions to reported intensities demonstrate that magnitude estimation accuracy is not necessarily indicative of ground-motion prediction accuracy. Perceived warning time distributions indicate that estimating maximum-expected warning times using the S-wave arrival is a reasonable assumption when discussing public EEW performance. However, we also find many reports of shorter warning times, late alerts, and missed alerts than expected based on ShakeAlert publication times, suggesting alert delivery latencies are substantial and highly variable. The novelty of our analysis is that we demonstrate that the DYFI EEW survey provides useful EEW efficacy information—independent of the specific alerting pathway—that can be used to inform our choices for conveying EEW performance.

California↗
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↗
USGS2026

A methods framework for evaluating measurement consistency across spectrometers for multispectral uncrewed aerial system vegetation mapping applications

The U.S. Geological Survey collects remote sensing data to support national scientific assessments of natural resources, hazards, and landscape change. Spectrometers and spectroradiometers are essential for gathering point-based spectral measurements used in applications such as uncrewed aerial systems (UAS) multispectral image calibration, validation, and analysis. Evaluating how different instruments perform in laboratory and field environments helps determine whether they provide consistent, interoperable measurements. Such verification can expand access to spectral ground data during UAS operations by allowing scientists to use alternative instruments when budgets, logistics, or field conditions limit options. We propose and test a methodological framework for evaluating spectrometers for measurement consistency during UAS multispectral vegetation mapping applications. There are three central evaluation components to the framework: laboratory, field, and relative to UAS multispectral imagery. By evaluating the instruments in both relatively controlled and uncontrolled environments, we thoroughly examine measurement consistency and when/why measurements may differ. We opportunistically selected two instruments for a case study in a coastal marsh setting: a compact laboratory spectrometer we modified for field use and a field-ready spectroradiometer. The instruments produced consistent measurements in both environments. We found differences between the field spectra and UAS spectra that likely reflect the perspectives of ground vs. aerial data and indicate that further radiometric calibration may be needed.

Massachusetts↗
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↗
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↗
USGS2025

Status of water-quality conditions in the United States, 2010–20

Degradation of water quality can make water harmful or unusable for humans and ecosystems. Although many studies have assessed the effect of individual constituents or narrow suites of constituents on freshwater systems, no consistent, comprehensive assessment exists over the wide range of water-quality effects on water availability. Using published studies, data, and models completed at regional or national scales in the United States during 2010–20, this chapter moves towards a comprehensive assessment by summarizing how selected anthropogenic and geogenic water-quality constituents affect national-scale water availability for human and ecosystem needs. Several types of human health, agricultural, ecological, and beneficial-use standards or thresholds were used to provide context for categorizing surface-water and groundwater quality. Water availability for human and ecological use is limited by elevated concentrations of geogenic and anthropogenic constituents in surface and groundwater. Elevated concentrations of five geogenic constituents (arsenic, manganese, strontium, radium, and adjusted gross alpha) are common in groundwater and collectively affect the drinking water supply to over 30 million people. Surface water sourced drinking water supplies are impaired in about a third of assessed stream miles, most commonly because of non-mercury metals and salinity. Health-based violations at community water systems may disproportionately affect socially vulnerable communities. Ecological water uses are predominantly limited by nutrients, sediment, temperature, pathogens, salinity, and pesticides. Water availability for human and ecological use is adversely affected by human activities including human contaminant sources (for example, wastewater, agriculture), processes (for example, dredging, groundwater pumping), or permanent landscape modifications (for example, dams, urbanization). Primary contaminant sources vary spatially and include fertilizer and manure, atmospheric deposition, wastewater treatment plants, urban land, and a range of natural sources. Contaminants of emerging concern, contaminants without regulatory thresholds, and mixtures of geogenic and anthropogenic water contaminants also contribute to ecological degradation and human exposure.

conterminous United States↗
USGS2026

Deaf, deafblind, and hard of hearing university student experiences with earthquake early warning in the United States: Evaluating language planning and technology access

The growing literature on deaf and hard of hearing (DHH+) populations and disasters demonstrates that emergency communication (including alerts) is not reaching global DHH + individuals with dangerous impacts for morbidity and mortality. This is the first research study in the U.S. to qualitatively explore the experiences of DHH + persons with earthquake early warning (EEW) through group-based dialogue sessions. The study investigates eight DHH + university students'past earthquake experiences, access to EEW alerts, and perceptions of ShakeAlert Ⓡ , an EEW system for detecting earthquakes and alerting residents of California, Oregon, and Washington. Findings highlight key gaps in disaster alert usability within four thematic areas: lack of messaging in participants' language(s), unclear alert messaging, deficient message delivery mechanisms for deafblind persons, and insufficient access to earthquake information and training that leads to dependence on informal information networks. Weaknesses identified in these four themes reduce DHH + trust in EEW systems and compromise the capacity of alert recipients to take swift protective action or to mentally prepare before shaking starts. The study also underscores structural factors such as insufficient linguistic representation in disaster language planning and technology design, which ignores the linguistic and sensory access needs of DHH + individuals. Building on disaster language planning frameworks, we recommend involving DHH + populations to co-develop EEW alerts. By centering DHH + perspectives, this research contributes to ongoing efforts to ensure that EEW systems reach everyone.

California↗
USGS2025

Ecohydrological response of a forested headwater catchment to a flash drought in the Southeastern U.S.

Flash droughts differ from traditionally defined droughts in their rapidity of intensification and often associated high vapor-pressure deficit. These droughts can lead to declines in streamflow and water table depth and induce water stress to vegetation at a greater rate than droughts that manifest over longer periods. However, little is known regarding the response of forested environments to flash drought because most studies of impacts have been conducted in agricultural settings. In this study we investigated water-use patterns of riparian trees using sap flow methods and examined the role of groundwater as a source of moisture over three periods that were delimited by antecedent soil moisture conditions. For a longer-term perspective we also examine monthly streamflow over the 35-year record. We observed that trees at only one monitoring plot showed a decrease in water use relative to evaporative demand during a flash drought. Total reverse sap flow (flow toward the roots rather than the canopy) greatly increased during the flash drought period, suggesting the likely occurrence of hydraulic redistribution to the excessively dry soils. Over the drought period groundwater became a more dominant source of moisture for sustaining forest water use. Monthly mean streamflow during the flash drought approached levels observed in past multiyear droughts. This is the first study, to our knowledge, to specifically investigate the response of multiple water budget components to flash drought in a humid forest. As more studies are conducted, a better understanding of the range of expected responses are likely to emerge.

Georgia↗
USGS2025

Observations of tear-drinking by lepidopterans on moose ( Alces alces americana ) in northeastern North America

Lepidoptera have long been known to feed on the tears of vertebrates as a presumed source of minerals or nutrients. While this unusual behavior has been observed in a variety of species, only a single previous record has been documented outside of the tropics. Here, we present the first documentation of moths visiting the eyes of a bull moose ( Alces americanus americanus ), captured via trail camera in Green Mountain National Forest, Vermont, United States. We discuss the biogeography of this behavior, how it may differ between tropical and temperate climates, and its potential impact on moose health.

Vermont↗
USGS2025

Estimated hydrogeologic, spatial, and temporal distribution of self-supplied domestic groundwater withdrawals for aquifers of the Virginia Coastal Plain

Water use from private-domestic wells accounts for nearly 40 percent of total groundwater withdrawals in the Virginia Coastal Plain Physiographic Province (henceforth called the Virginia Coastal Plain). However, because self-supplied domestic water use generally falls below the Virginia Department of Environmental Quality (VDEQ) reporting and management threshold of 300,000 gallons per month, quantifying these withdrawals is challenging. This report builds upon the foundation of previous U.S. Geological Survey investigations by providing revised techniques to improve estimates of the aquifer source, spatial distribution, and monthly magnitude of these groundwater withdrawals. The aquifer sources of private-domestic wells in the Virginia Coastal Plain were estimated by cross-referencing 8,264 well records from the VDEQ and the Virginia Department of Health to a digital model of the Virginia Coastal Plain hydrogeologic framework. This analysis highlights the regional importance of the Yorktown-Eastover, Potomac, and surficial aquifers. Collectively, these three aquifers account for 80 percent of self-supplied domestic groundwater withdrawals. The population using self-supplied domestic water was estimated using census blocks, well-use ratios, building footprints, and land-use and land-cover data to produce a high-resolution, disaggregated, raster-based dataset. This approach improves upon previous models at the census-block or road-network scale by reducing the low-density spread of the self-supplied domestic population across undeveloped areas and concentrating the population and its corresponding water use in the areas where it is most likely to occur. Results show that an estimated 475,332 people comprise the 2020 self-supplied domestic population of the Virginia Coastal Plain, an increase of 5.7 percent since 2010, and the greatest concentrations of self-supplied domestic population surround large cities. Estimates could be further refined with the addition of current and complete spatial data on public water-system service areas. The quantity of water used by the self-supplied domestic population was estimated by modifying published state per-capita water-use coefficients with the corresponding monthly variability assessed from Virginia Coastal Plain public water-system withdrawal data. This analysis estimates an average increase of 12 percent from June through August and an average decrease of 8 percent from December through March from the baseline annual average of 80 gallons per day per capita, which generally matches similar studies in the eastern United States. The application of these revised methodologies for the estimation of private-domestic wells and the self-supplied domestic population improves understanding of domestic groundwater use in the Virginia Coastal Plain across hydrogeologic, spatial, and temporal scales. These revisions help better inform water-resource managers and decision makers and support higher resolution groundwater modeling. Furthermore, these methods are transferrable to other areas where self-supplied domestic water withdrawals are important to the overall water budget.

Virginia↗
USGS2026

Decadal shifts in groundwater age detected by environmental tracers across California, USA

Groundwater age offers important insight into recharge, storage, and contamination risk. Although models predict age changes can be driven by pumping and climate variability, direct observational evidence remains limited. Here, we analyzed paired environmental tracer suites (tritium, carbon-14, and tritiogenic helium-3) collected a decade apart from 268 wells across California to assess the prevalence of groundwater age transience. Travel-time distribution models and statistical tests indicated age transience at 29% of sites, occurring most often in agricultural regions, such as the San Joaquin Valley and Southern Coast Ranges, where large carbon-14 changes coincided with substantial nitrate and chloride shifts. Sites with tritiogenic helium-3 data showed more frequent age transience, underscoring the value of multi-tracer data sets. These results provide the first regional evidence of widespread groundwater age change and a method for detecting changing water balances with implications for groundwater sustainability and water quality.

California↗
USGS2025

Groundwater surveillance of swine pathogens from private wells supplying swine farms in Iowa

Biosecurity practices are essential for maintaining pig health and productivity. Despite these measures, pathogen spread still occurs. Water is one of the largest daily inputs on swine farms by volume and is not routinely tested or disinfected before it is consumed by the animals [1-3], making it a poorly understood biosecurity risk. Groundwater from privately-owned wells is a common water source for swine farms. Pathogens in the landscape, such as bacteria, viruses, and protozoa, can reach groundwater more rapidly through soil macropores, maintaining viability and facilitating transmission of pathogens into aquifers [3-13].

Iowa↗
USGS2026

Investigation of drivers and sources of potential harmful algal blooms in Lake Anna, Virginia, 2023-24

Algal blooms in freshwater reservoirs are an increasing concern because of the risk to aquatic ecosystem health, recreational use, and water quality. Among the taxa that comprise an algal bloom, cyanobacteria are of particular concern due to the potential to produce toxic compounds which can cause acute and chronic illness in humans if ingested through contaminated water or shellfish. When toxins are above a toxin-specific threshold in the water column, the Commonwealth of Virginia categorizes the bloom as a harmful algal bloom (HAB), distinguishing it from an algal bloom without toxins present. Toxins are of particular concern in bodies of water which serve as major recreational areas, such as Lake Anna in central Virginia. Lake Anna is a 27 km-long and 47 km2 reservoir in central Virginia. Since the Commonwealth of Virginia revised the HAB monitoring framework in 2018, algal bloom advisories for potentially toxigenic blooms have been issued in the western, riverine zone of the reservoir. There were detections of microcystin and anatoxin production but no detections of cylindrospermopsin and saxitoxin production in Lake Anna; however, toxin concentrations were low, at values less than 0.65 µg/L. In 2023, the U.S. Geological Survey, in cooperation with Virginia Department of Environmental Quality, initiated a 19-month intensive and extensive study of western Lake Anna and its tributaries (North Anna River and Pamunkey Creek) to (1) characterize the algal community, biomass, and toxin production; (2) identify potential drivers leading to algal bloom initiation, persistence, and decline; and (3) assess the primary sources of the drivers contributing to algal blooms. Continuous and discrete monitoring of water quality within the lake, watershed inputs, meteorological conditions, and algal communities were monitored. Multiple modeling scenarios identified that the formation and persistence of algal blooms in Lake Anna are driven by interactions among chemical, macro- and micronutrient, and physical factors. Key drivers include total nitrogen, total phosphorus, water temperature, suspended sediment concentration, wind speed, copper, iron, molybdenum, nickel, sodium, and alkalinity. During this study, winter stormflow events delivered the highest loading of macro- and micronutrients from the tributaries to the lake. The lake is a sink for these nutrients in the water column or in the lake-bed sediments. During high-occupancy and recreation periods on the lake in the summer months, boating activity can promote internal loading by the resuspension of the lake-bed sediments, thereby increasing the nutrient availability for algal uptake. Thermal stratification and hypoxic conditions were observed, which can contribute to the passive release of nutrients into the water column, further facilitating algal bloom proliferation. These processes may create a positive feedback loop that supports the formation, persistence, and annual recurrence of algal blooms in the western region of Lake Anna. Continued water-quality monitoring of early warning indicators may improve the detection and forecasting of algal growth in the lake and help managers proactively manage water quality and algal growth.

EarthArXiv↗