Geology topics

Research about contiguous United States

Source-linked reports with geographic coverage including contiguous United States.

At least 19 recordsLinked to original sources

USGS2026

National-scale remotely sensed lake surface temperature in the contiguous United States

Temperature is a master variable in aquatic ecosystems. Despite its importance for ecosystem function, our capacity to measure temperature is often limited to focal systems with intensive in situ measurements or larger systems with readily accessible data from disparate data streams. These limitations are consequential for holistically understanding aquatic ecosystem status and change, especially considering that most lakes globally do not have consistent in situ data. To empower researchers with macroscale surface temperature observations, we present the first remotely sensed lake temperature dataset that includes measurements from Landsat 8 made every ~ 16 d for 137,394 lakes of at least 4 ha in surface area throughout the contiguous United States from 2013 through 2025. By aggregating data in a cloud computing framework, the dataset is amenable for continual update, thereby allowing end users to track local-to-continental scale changes in lake water temperature over time.

contiguous United States↗

USGS2026

Sediment vulnerability ranking for river basins across the contiguous U.S. using integrated biophysical and social-ecological data

Nearly half of streams and rivers in the United States (U.S.) have fair to poor conditions for aquatic ecosystem health as declared by the U.S. Environmental Protection Agency, and sediment was identified as a primary factor impairing these waterbodies. We rank sediment vulnerability using physical, ecological, and socioeconomic datasets in 163 4-digit Hydrologic Unit Codes within 18 regions across the contiguous U.S. based on the National Hydrography Dataset. We refer to sediment vulnerability as the potential for excess sediment to adversely impact social-ecological aspects of streams and rivers. Metrics were organized into six variable groups: (1) geomorphic setting, (2) modeled sediment and phosphorus, (3) hydrologic conditions, (4) anthropogenic factors and land use, (5) socioeconomic considerations, and (6) measures of ecosystem sensitivity. Correlations and principal component analysis were used to reduce and select metrics that explained the highest variability across basins. Results from the regional analysis identify basins with higher sediment vulnerability in each region, whereas national results identify hotspots of highly ranked basins in the Midwest and the central U.S. with a concentration of moderately to highly ranked basins in the south-central and southwestern U.S. Indicators of socioeconomic and ecological vulnerability integrated with physical drivers of sediment production help identify important gaps in sediment monitoring and research.

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USGS2026

Cyanobacteria Assessment Network: Pilot study with Sentinel-2 derived chlorophyll data

Harmful algal blooms (HABs) affect global water quality, limiting uses like recreation and consumption because of excessive algal biomass and toxin production. These blooms cause surface scums, taste and odor issues, hypoxia, and negative health and socioeconomic impacts. The US Army Corps of Engineers (USACE) manages over 400 lakes and reservoirs and seeks to improve monitoring of HABs through Sentinel-2 (S2) satellite imagery. The purpose of this project is to develop workflows for a national chlorophyll-a product with 20 m spatial resolution, enabling HAB monitoring for over 270,000 lakes and reservoirs. The 1-year pilot study established a federal partnership to conduct preliminary S2 processing steps, using datasets from Florida, Ohio, and Oregon. Key steps included in situ data aggregation, data assimilation, S2 algorithm evaluation, spatial and temporal compositing, satellite sensor cross-validation, and web hosting of an example prototype product. The study covers 29 USACE reservoirs, with cross-validation using Sentinel-3 (S3) data from 212 lakes. The multiagency initiative aligns with federal agency missions to protect health and the environment, supports acts like the 2017 Harmful Algal Bloom and Hypoxia Research and Control Act, and has annual potential avoided costs of $42 million.

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USGS2026

Evaluating interactive effects of the Conservation Reserve Program and wind energy infrastructure on grassland bird abundance in the United States

The extent of grasslands has contracted globally, leading to significant declines in grassland-obligate species, including birds. Grassland birds are threatened by multiple factors, including grassland conversion to cropland, and development, including energy infrastructure. In the USA, the federal Conservation Reserve Program (CRP) provides financial incentives for agricultural landowners to convert marginal cropland to vegetative covers, including grassland, making it a key approach to recovering grasslands. However, given the high percentage of wind turbines near Conservation Reserve Program land, it is critical to determine if wind energy and the Conservation Reserve Program interact to affect grassland birds. We used generalized additive models and community science eBird data to assess the interactive effects of wind and the Conservation Reserve Program on the abundances of 27 grassland-obligate bird species across their breeding ranges in the continental US. We found associations between bird relative abundances and interactions involving wind and Conservation Reserve Program variables, suggesting that wind energy development near Conservation Reserve Program fields could dampen the benefits of the Conservation Reserve Program for some species. These results indicate that decisions about where to install wind energy infrastructure that incorporate information about the presence of Conservation Reserve Program land may reduce the adverse effects of wind energy on grassland birds. This study provides information that can help maximize the benefits of the Conservation Reserve Program while allowing for environmentally friendly development of renewable energy.

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USGS2026

A roadmap for identifying and interpreting physical processes and national water model prediction bias associated with baseflow index regimes across the contiguous United States

Understanding how groundwater–surface water interactions shape streamflow variability is critical for diagnosing low flow behavior and prediction bias in continental scale hydrologic models. We present a process informed framework that links observed baseflow (BF) dynamics, watershed attributes, and National Water Model (NWM) performance across the contiguous United States. Using daily observed streamflow from 797 reference quality streamgages, we developed monthly baseflow index (BFI) signatures using a streamgage specific, calibrated digital filter. Hierarchical clustering of these signatures identified seven distinct BFI regimes capturing regional and seasonal variability. We evaluated NWM v3.0 retrospective streamflow performance within each regime using multiple hydrograph and flow duration curve-based metrics. Model skill varied systematically across regimes: mixed flow systems were simulated most accurately, while predominantly BF dominated and quickflow dominated regimes exhibited substantially poorer performance. Across nearly all regimes, the NWM underestimated observed BFI magnitude and frequently failed to reproduce seasonal BF patterns, indicating systematic biases in simulated low flow contributions. To relate these regimes to potential process controls, we trained a Random Forest classifier using static watershed attributes and applied Shapley Additive Explanations to identify features most strongly associated with each regime. Results highlight regionally varying influences, including the dominant role of snow fraction and seasonal runoff timing in snow dominated basins and the importance of evapotranspiration and aridity in quickflow dominated systems. Collectively, these findings demonstrate how hydrologic signatures combined with interpretable machine learning can diagnose regime specific model biases and generate process-based hypotheses about limitations in large scale hydrologic prediction systems.

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USGS2026

Current and near-future conditions of aquatic spatial data for use in ecological models in the United States

To address increasing demand for ecological models of aquatic species that can inform the management of national freshwater resources, we leveraged manager input to develop suites of environmental data layers characterizing freshwater habitats for the contiguous United States. Using the National Hydrography Dataset, these new data cover lentic and lotic systems under current and near-future environmental conditions. The data include a variety of covariate categories including climate, soil chemistry, land use and land cover, and human modification of the surrounding landscape. The predictor resolution for atmospheric climate predictors was the lake (wetland) or stream reach, and, for the terrestrial proxies, the subwatershed (HUC12) surrounding the lake or stream reach was chosen to capture the relevant land features surrounding the habitat. Future land use, land cover and streamflow predictions were included from present to mid-century. These data are available for the development of freshwater ecological models in the contiguous United States for a variety of applications, including species distribution modeling and exploring change in spatially diverse aquatic systems in time.

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USGS2026

A multi-state assessment of per- and polyfluoroalkyl substances (PFAS), pesticides, and antibiotic resistance genes in white-tailed deer (Odocoileus virginianus) of the United States

Sentinel species provide a vital One Health perspective on ecosystem contamination driven by rising global chemical production. We evaluated white-tailed deer ( Odocoileus virginianus ; n = 54, 24 states, six matrices) as nationwide bioindicators for PFAS, pesticides, antimicrobial resistance (AMR) genes, and microbiome diversity. PFAS were detected in 100% of deer samples (26 compounds identified overall; non-detect to 12.3 ng/g ww), with preferential accumulation in the liver, indicating widespread systemic exposure. Neither region, landscape, nor source proximity predicted liver PFAS concentrations, whereas landscape had a significant, albeit weak, effect on spleen concentrations. This overall absence of strong spatial drivers suggests ubiquitous background contamination rather than localized point-source exposure. Conversely, 13 pesticides/transformation products (ranging from non-detect to 88.6 ng/g ww; highest in scat) were detected in only 28% of samples, despite widespread national use. Since not all possible transformation products were measured, these data reflect the accumulation of the target compound rather than total pesticide exposure. Driven by the rapid metabolism and excretion of herbicides, persistent insecticides dominated tissue samples. Additionally, biological threats were prevalent with eight distinct AMR genes identified in WTD scat, frequently featuring the florfenicol resistance gene (flo st, 33%). The presence of synthetic compounds and AMRs in game meat and scat pose a direct One Health risk to the human food chain. These findings highlight the value of using a single, widely distributed sentinel species as an early warning system for the ecological and public health threats posed by global chemical pollution.

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USGS2025

The US EPA’s National Nutrient Inventory: Critical shifts in US nutrient pollution sources from 1987 to 2017

Efforts to constrain the negative environmental impacts of excess nitrogen (N) and phosphorus (P) are costly and challenging, due in part to inconsistent reporting of nutrient sources at temporal and spatial scales relevant for local decision making. To meet this challenge, the U.S. Environmental Protection Agency’s National Nutrient Inventory provides estimates of major agricultural, urban, atmospheric, and natural nutrient fluxes for the contiguous United States at county and HUC12 scales annually from 1987 (from 1950 for agriculture) to 2017. Since the late 1980s, total N emissions and atmospheric N deposition have declined 22% and 15%, respectively, despite increased agricultural emissions. Over the same period, municipal wastewater N and P loads remained largely stable, despite population increases, through wastewater treatment upgrades and the phaseout of phosphorus-containing detergents. Improved agricultural efficiency allowed for dramatic increases in agricultural production and crop harvest since 1987 (∼25% for N and P), with little change in surplus nutrients left on fields. Overall, a combination of innovative technologies and management has stemmed or even decreased major sources of nutrient pollution to the environment over the last several decades, representing an important shift that, if continued, may contribute to improved air, land, and water quality and human health.

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USGS2025

Geothermal potential of orphan oil and gas wells

The United States is estimated to have hundreds of thousands of orphan oil and gas wells. Orphan wells are abandoned wells that are both unremediated and have no responsible operator. While traditionally considered environmental and economic liabilities, orphan oil and gas wells may offer new opportunities in sustainable geothermal energy development. This study evaluates the potential of repurposing orphan wells for geothermal energy production. We analyzed more than 1.4 million bottom-hole temperature (BHT) records from oil and gas well logs to create corrected temperature-depth profiles in a grid across the United States. Total depth values, where available, in documented orphan wells from a U.S. Geological Survey (USGS) database were then correlated to these temperature-depth profiles to estimate a corrected BHT for each orphan well. The orphan wells were then categorized as having low (<90°C), moderate (90–150°C), and high (>150°C) geothermal potential, identifying them as wells in the U.S. that could be used to access geothermal resources. In addition, repurposing these wells could contribute to broader environmental and economic goals, including well remediation, rogue methane emissions reduction, and energy production. This study provides a framework for integrating inactive well inventories with geothermal resource assessments and further highlights the potential for orphan wells to play a transformative role in expanding geothermal energy capacity in the United States.

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USGS2025

Twenty years (2000-2020) of butterfly monitoring data across the contiguous United States

We present the most comprehensive, integrated, butterfly monitoring dataset ever assembled for the United States. It contains over 1.2 million count records, from 65,000 surveys, representing over 12.6 million individual butterflies. To compile this dataset, we integrated data and harmonized taxonomy across 19 butterfly monitoring programs in the United States – one national, 13 statewide, and 5 local (e.g. individual county or National Park) in scale. In addition to the data, we also provide the taxonomic dictionary used to crosswalk butterfly taxonomy across programs, and the code used to assemble the integrated dataset. The publication of this dataset will inspire new analyses of butterfly population trends and drivers that help to identify solutions to the biodiversity crisis.

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USGS2025

U.S. Geological Survey geomagnetic variometer data: Capitalizing on seismic infrastructure

The U.S. Geological Survey’s Geomagnetism Program is collaborating with the Earthquake Hazards Program and Global Seismographic Network Program to densify magnetic field observations. This collaboration focuses on the installation of magnetometers, or magnetic variometers, at existing seismic stations. Along with improving the density of space weather observations for hazard monitoring, these data can be used to correct colocated magnetic field induced noise in seismic data. Such corrections are especially useful during time periods of large magnetic storms where the magnetic field‐induced instrument noise can be of similar amplitude to earthquake ground‐motion records.

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USGS2025

Mapping a Carrington storm

A map is presented of median 1-min-resolution peak geoelectric-field strength across the United States as would be induced by magnetic storms as intense as the 2 September 1859 Carrington storm. The map is constructed from two data sets: Magnetometer time series from 22 ground-based observatories recording 40 magnetic storms, and surface impedance tensors derived from magnetotelluric measurements acquired at 1616 survey sites across the contiguous United States. Carrington-class storm geoelectric fields are likely to be very strong in the United States East and Midwest; > 5.00 V/km at many places. In Virginia, strengths would likely range from 30.30 V/km, with a 68% confidence interval of [19.44,47.20] V/km, to as low as 0.05 [0.03,0.07] V/km. Comparison of model geopotentials with those measured on 30 long lines, indicates errors of about 18%. A Carrington-class storm would likely induce geoelectric fields with strengths 55% greater than for the 13–14 March 1989 storm.

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USGS2025

Modeling current and future distribution of invasive tegu lizards along geopolitical boundaries in the contiguous United States: Implications for invasion threat

Historically, constrained temperature ranges limited the spread of invasive herpetofauna into temperate climates, but climate change is predicted to facilitate broader distributions. There are three species of tegu lizards native to South America and available in the pet trade that have a high risk of invasion and deleterious impacts to native ecosystems in the United States (US). There are four populations of the black and white tegu ( Salvator merianae ) in Florida and sightings as far north as North Carolina and west as California. Red tegus ( S. rufescens ) have been observed in Florida, and there is an established population of gold tegus ( Tupinambis teguixin ) in Florida. We updated previous distribution models for the contiguous United States (CONUS) that used occurrence points from their native range in South America to evaluate potential changes given current and future climate scenarios (+2 °C and +4 °C warming). Under current climate conditions, one or more tegu species have the potential to occupy most ecoregions in the CONUS. Under a + 4 °C warming scenario, suitable habitat increases by 11 % for S. merianae , 31 % for S. rufescens . The proportion of suitable habitat for T. teguixin was small under all scenarios, but increased from 0.0003 to 0.0017. For S. merianae , parts of Florida become less suitable, while suitability increases in this region for the other two species. Additionally, much of the western US is projected to be suitable for S. rufescens . Our case study underscores the potential for climate change to compound invasion threats that could outpace effective managerial responses.

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USGS2025

Regional patterns in U.S. wildfire activity: The critical role of ignition sources

As extreme wildfires increase globally, understanding their causes is critical for effective management. While climate and housing growth are commonly linked to rising fire activity, the role of specific ignition sources—particularly human-caused—remains understudied. Analyzing a 79-year dataset (1940–2019) from U.S. Forest Service regions across the continental United States, we found that different ignition sources in different regions have been a major driver of wildfire trends, accounting for 60%–80% of the interannual variation in fire frequency and approximately 20% in area burned across most U.S. regions. Lightning and campfires were the dominant sources in western regions, while arson drove fire activity east of the Mississippi River. Trends also varied significantly by region and over time, with housing growth explaining more in terms of fire frequency and climate primarily influencing area burned. Importantly, frequent fires often originated from different sources than those causing the largest areas burned. Prevention of human-caused ignitions, such as campfires and arson, could offer efficient and effective strategies to mitigate wildfire impacts on human and natural systems under changing climate and land-use conditions.

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USGS2025

Ecologically informed solar enables a sustainable energy transition in U.S. croplands

United States (U.S.) croplands are ideal recipient environments for solar photovoltaic (PV) energy because they are flat and have a high solar resource. Perceived threats of solar to agriculture have led some stakeholders to suggest that croplands be exclusively used to produce food. However, 12 million hectares of U.S. croplands, an area about the size of New York State, are already dedicated to corn grown for ethanol (i.e., biofuel), an energy product that requires significantly more land than solar PV per unit energy. Ecosystem service benefits of an ecologically-informed approach to solar development (i.e., ecovoltaics), coupled with significant land-use advantages over corn ethanol, make solar an attractive solution for a sustainable energy transition in croplands. Here, we evaluated how the conversion of a small fraction of corn-ethanol croplands into ecovoltaic solar facilities might improve land-use efficiency of energy generation, enhance ecosystem services, and provide landscape diversification. Through spatial analyses, we determined that converting just 3.2% of land currently used for corn ethanol would increase the share of utility-scale solar energy in the U.S. from 3.9% to 13%. We also identified target locations where strategic conversion of corn ethanol to solar PV co-located with perennial vegetation could filter excess nutrients transported from adjacent farm runoff, diversify and connect agricultural landscapes, and provide local wildlife habitat. In contrast to the common perception of land-use competition and land scarcity in the energy transition, our findings highlight benefits of co-located energy landscapes that integrate fundamental principles of energy development and sustainable agroecosystems.

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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.

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USGS2025

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

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

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USGS2025

Cyanotoxin and domoic acid occurrence, relation with salinity, and potential recreational health risks in U.S. coasts in the 2015 US EPA National Coastal Condition Assessment

In the first nationwide study of cyanotoxins in U.S. estuaries, algal toxins, cyanotoxins, chlorophyll, and salinity were measured in samples collected during the National Coastal Condition Assessment 2015. Anatoxin-a (ANAA), cylindrospermopsin (CYLS), domoic acid (DMAC), and microcystins (MCs) were detected by LC/MS/MS in 0.6, 0.9, 8.3, and 2.0 % of samples with mean concentrations of detections of 0.13, 0.13, 0.53, and 0.49 µg/L, respectively. MCs by ELISA were also evaluated, and 4.0 % of samples had measurable MCs with a mean of 0.78 µg/L. While ANAA and CYLS were detected south of 40° latitude, MCs by ELISA and DMAC occurred nationwide. Results were compared to freshwater recreational health thresholds from the World Health Organization and US Environmental Protection Agency to evaluate potential recreational exposure to MCs and CYLS since marine thresholds do not currently exist. Cyanotoxins were categorized using the 2021 World Health Organization Alert Level Framework for recreational exposure with 99.4, 99.1, 94.7, 98.0, and 44.7 % of samples being at the Vigilance Level for ANAA, CYLS, MCs (ELISA and LC/MS/MS), and chlorophyll, respectively with the remaining samples at Alert Level 1. Chlorophyll had 19.9 and 9.9 % of samples at Alert Level 1 and Alert Level 2, respectively. All cyanotoxins were below US EPA health advisory thresholds. ANAA, CYLS, DMAC, and MCs by ELISA were detected in samples with a wide range of salinities, while MCs by LC/MS/MS only occurred in samples with salinity <5 part per thousand (PPT). The source of cyanotoxins is likely a combination of inland transport and in situ estuarine production.

contiguous United States↗