Geology topics

Research about conterminous United States

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

At least 37 records · Page 2Linked to original sources

USGS2026

Tropicalization of the temperate zone: Spatiotemporal variability of winter warming and declining freeze days across the United States

We investigate changes in cool-season and winter daily minimum (T min ) and maximum (T max ) temperatures, and the occurrence of freeze days, from 1952 to 2024 across the conterminous United States (CONUS). Emphasis is placed on the tropical-temperate transition zone (TTTz) in the southeastern CONUS. During winter, ~70% of the land area exhibited T min warming rates exceeding those of T max . The countywide coldest T min became milder across 57% of the CONUS, while the coldest T max showed little change and even cooled east of the Rocky Mountains in the central CONUS. Across the TTTz, 75% of freeze days occur within a ~25–100-day window, often fewer than 75 days in the southernmost areas. Approximately 80% of counties exhibited significant contractions in freeze-day concentration, with the largest and most spatially consistent changes occurring in the Southeast, primarily driven by later start dates. Roughly 85% of the CONUS experienced a significant decline in freeze days, with the largest relative declines in regions where average winter T min is above freezing, while parts of the Pacific Northwest showed no significant change. An analysis of freeze day isopleths (30, 45, 60 and 75 days) across 20-year periods showed that the mean latitude of freeze days has migrated poleward substantially. Between 101° W and 79° W in the TTTz, the 30 freeze-day isopleth for the late period (2005–2024) was, on average, 122 km (~1.1° latitude) farther north than in the early period (1952–1971). Generally, the largest latitudinal shifts and percentage losses in freeze days occurred across low-elevation, low-relief regions at lower latitudes (e.g., the Mississippi River Valley), with abrupt shifts occurring near topographic gradients. Regions with sharp elevational gradients (e.g., Balcones Escarpment, Ouachita Mountains and Tennessee Valley) exhibited smaller temporal changes, likely reflecting the barrier-like influence of higher terrain on the poleward retreat of freeze days.

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USGS2026

Riverine pesticide trends in the United States: Assessing a decade of national-scale monitoring

Pesticides in freshwater systems can compromise water availability by degrading water quality, with implications for human health and aquatic life. Despite recognition of the need for national-scale monitoring and analysis, few studies have documented long-term trends in surface water pesticide contamination across the US. This study addresses that need by analyzing temporal trends and acute and chronic benchmark exceedances for aquatic life and human health from 81 river sites sampled from 2013 to 2022 using an analytical method targeting 80 pesticides. The majority (79%) of single site and pesticide combinations had too few pesticide detections to estimate trends. When detections were more frequent, increasing trends in concentration were twice as common as decreasing trends. Increasing pesticide concentrations were common in primary drainages of the Mississippi River Basin. Aquatic life benchmarks were exceeded by 19 pesticides, and exceedances were geographically widespread, with both acute and chronic aquatic life benchmark exceedances at 62% of sites. The herbicides atrazine and metolachlor and the insecticide imidacloprid were identified as the greatest threats to surface water availability based on their trends and aquatic life benchmark exceedances. These findings demonstrate the need for continued monitoring and trend analysis, driver investigation, and management strategies to protect freshwater resources.

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USGS2026

Inland recreational fisheries harvest far exceeds reported inland harvest in the United States

Recreational fisheries are important global contributors to food security, socio-cultural practices, and local and regional economies. However, inland recreational fisheries are often overlooked by policymakers due to a limited understanding of the magnitude of participation, harvest, and economic impact. Here, we used the U.S. Inland Creel and Angler Survey Catalog and catch and effort model (CreelCatch) and several assumptions to provide an initial estimate of the magnitude of total inland recreational fisheries harvest in the conterminous USA. The CreelCatch model projected fishing harvest across lakes, ponds, and reservoirs based on fishing effort, water body area, and regional effects. We estimated that recreational lake fisheries in the conterminous USA likely harvest 236,000–671,000 tonnes of fish per year, 17–48 times greater than total inland fisheries harvest reported to the United Nations. Inland recreational fisheries may warrant greater consideration for their contribution to national scale socioeconomics and impacts on fish stocks and ecosystems.

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USGS2026

Identifying potential invasion hotspots for non-native fluvial fishes throughout the conterminous United States

Identifying habitats that non-native fluvial fishes are likely to invade provides information for proactive management, conservation planning, and understanding the ecology of biological invasions. We identified streams in the conterminous United States with high invasion risk from 20 non-native fluvial fish species. Specifically, we (1) developed habitat suitability models for each species using nine natural and six anthropogenic predictors within nine large ecoregions, identifying the potential invasion hotspots; (2) evaluated the relative importance of natural and anthropogenic predictors for each species; and (3) assessed potential invasion risk to protected stream habitats. Predicted invasion hotspots included much of Florida, coastal regions of Texas and Louisiana, and areas surrounding major metropolitan centers such as Chicago, New York, and Phoenix. Model predictions indicate that goldfish ( Carassius auratus ), pirapitinga ( Piaractus brachypomus ), and pond loach ( Misgurnus anguillicaudatus ) could occupy extensive suitable habitats across the conterminous United States. The most influential natural predictor across species was network catchment area (a surrogate for stream size), while the most influential anthropogenic predictor was human population density. Goldfish were predicted to be present in protected areas across all nine ecoregions, highlighting their high invasion potential. Collectively, our results provide critical information on regions vulnerable to invasion and the species most likely to become established and identify areas at risk of invasion within protected landscapes.

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USGS2026

The United States Magnetotelluric Array and the National Impedance Map

The United States Magnetotelluric Array (USMTArray) data set, collected in the years 2006–2024, consists of more than 1,700 long-period magnetotelluric stations covering the entirety of the contiguous United States on a quasi-regular 70 km grid. Funding across multiple federal agencies was critical to sustaining this effort to its completion. Important components of the project included active guidance and participation from the MT community, the open and timely availability of all data, and the application of consistent instrumentation and robust data processing. Together with parallel advancement in the development of publicly available three-dimensional (3D) inversion codes, the USMTArray has revitalized the US magnetotelluric community and increased the visibility of magnetotellurics within the Earth-science community. Taken as a whole, these data are visualized as the National Impedance Map, which, together with a 3D synthesis conductivity model of the nation, reveals the electrical architecture of the contiguous US. USMTArray data are used by researchers worldwide for fundamental and applied studies, including investigations of continental architecture and evolution, estimation of hazards to critical infrastructure due to geomagnetic storms, and assessment of the nation's undiscovered geothermal and mineral resources. We here review the history and development of the project, discuss the challenges and successes in its execution, present the National Impedance Map and synthesis conductivity model, and highlight the breadth of research stemming from this rich data set.

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USGS2026

Aligning legacy NLCD land cover maps based on Landsat Collection 1 to Collection 2

The transition from Landsat Collection 1 to Collection 2 introduced significant improvements in radiometric and geometric accuracy. However, the improvements cause location misalignment between the existing Landsat-derived land cover products and the new collection. The legacy National Land Cover Database (NLCD) has been used as a cornerstone land cover source for a variety of research. Therefore, a method aligning the legacy NLCD product to Collection 2 is required to ensure its continuity and consistency of service. We developed a strategy to not only align legacy NLCD to match new Collection 2 geometric locations but also improve land cover labeling in the region that was affected by the geometric shifts. The method identifies boundary pixels of homogeneous land cover patches as potential problem areas that are likely impacted by geometric shifts and generates candidate labels from 3 × 3 window with the target pixel at the center and segmentation-derived majority label. Standard phenology patterns of each candidate land cover type are established based on the random samples except boundary pixels within a 1000-pixels × 1000-pixels processing window region. The phenological distance to each standard land cover type pattern is calculated through a penalty dynamic time warping (DTW) method for each target pixel in the boundary region. Finally, the method determines the most suitable label based on the phenological distance from the candidate labels. Both visual and accuracy assessment results demonstrate that the alignment preserves the overall land cover patterns in the original legacy NLCD product while reducing the spatial discrepancies between the Landsat Collection 2 and land cover. In addition, it enhances the accuracy of land cover labeling of boundary pixels. The overall accuracy (OA) was increased by 7% in the land cover boundary regions after alignment. The quality and confusion matrix comparison between the alignment results and the original legacy NLCD confirm the reliability of the method. Our alignment method has the potential to serve as a framework for aligning other Landsat-derived land cover products to future collections.

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USGS2026

Metallurgical coal—Deposits, production, resources, market dynamics, and supply chain risks

Plain Language Summary Metallurgical coal (met coal; consumed to produce coke for steelmaking) must meet specific chemical and physical specifications. In 2023, the conterminous United States produced 66 million short tons (mst) of met coal, consumed 15.85 mst domestically, exported 51.1 mst, and imported 0.7 mst. Most met coal was produced in the Appalachian Basin, but there are also resources that meet the specifications for met coal in the Western United States.

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USGS2026

Thematic accuracy assessment of the National Land Cover Database (NLCD2021) for the conterminous United States

The MultiResolution Land Characteristics (MRLC) consortium’s National Land Cover Database (NLCD) was established as an operational, stakeholder-oriented land cover monitoring program with the release of the NLCD2001 database. Both land cover and land cover change data became available with the release of NLCD2006. Here, we report the land cover and land cover change accuracies for NLCD2021, documenting Level II and I accuracies for the 2016, 2019, and 2021 land cover datasets and 2016–2021 land cover change. An additional objective, not addressed in previous NLCD assessments, is the estimation of the total variance of area estimates, where total variance includes sampling variance and variability in reference label assignment. We estimate the total variance of the area estimates for the stable and change classes targeted by the strata used in the sampling design. For the 16 Level II classes, the overall accuracy (OA) was 73% ± 1% when agreement was defined using only the primary reference class label and 89% ± 0.7% when agreement was defined as a match between the map label and either the primary or alternate reference label (± standard error, SE). For the eight Level I classes, the corresponding OA estimates were 81% ± 0.9% and 89% ± 0.7%. Level II and Level I OA tended to be higher for 2016 land cover and lower and more similar for 2019 and 2021 land cover. Land cover change user and producer accuracies (UA and PA) tended to be <50%. When the alternate reference label was included in the definition of agreement, exceptions of high class-specific accuracies (≥75%) were more prevalent for PA than UA. The consistency of reference label interpretations was greater for no-change classes than for change classes. The estimates of the total variance incorporating interpreter variability were often smaller than the standard variance estimates, indicating the possibility that the total variance estimator is highly unstable. Further study is needed to improve the utility of this total variance estimator for practical applications.

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USGS2026

Local water use and climate variability drive water stress and alter ecological flows over the conterminous United States

Consistent, large-scale estimates of water availability are needed to identify and avoid potential conflicts among human and ecosystem uses of water. We present an assessment of water limitation, defined as the monthly balance (difference) between water supply ( ws ) and human consumptive water use ( wc ), for the conterminous United States (CONUS) during water years 2010–2020. We estimate that 26.7 million Americans, 8% of CONUS population, live in areas with chronic high or severe water limitation. Although ws greatly exceeds wc at the CONUS scale, water is limited locally or regionally due to spatial and temporal patterns in climate and wc . Our water limitation metric, the monthly supply and use index (SUI), peaked in 2012 during a widespread drought when 38% of the CONUS land area experienced elevated water stress. The central and Southwestern U.S. experienced the highest SUI due to the combination of low ws and high wc , especially for irrigation. Spatial overlays of SUI and fish habitat ranges, including those of conservation concern, revealed that several species had notable proportions of their habitat exposed to high or severe water limitation during spawning season over the modeled time period, especially the Arkansas River shiner. ws was calculated from two CONUS, physically-based, hydrologic models while wc was calculated from three CONUS models of water use for crop irrigation, thermoelectric power generation, and public supply. The ws and wc values were routed through a stream network and compared to calculate water limitation and SUI for human populations and fish species at the scale of 12-digit hydrologic unit codes. Evaluation of water availability at higher spatial and temporal resolution promotes more comprehensive analyses of the drivers of water availability and can be combined with complementary studies of water quality and water limiting thresholds to better understand the limitations on water availability.

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USGS2026

Potential impacts of groundwater pumping on stream temperature are greatest in streams with substantial cold groundwater inflows

Groundwater pumping-induced reductions in streamflow (known as ‘streamflow depletion’) have been documented worldwide, but potential impacts of streamflow depletion on stream temperature are not well understood. Here, we use two types of models to identify potential impacts of pumping on stream temperature across the conterminous United States (CONUS) to determine which aspects of a stream's annual thermograph (thermal signatures) can be used to monitor and manage streamflow depletion impacts on stream temperature. We used long-term streamflow and stream temperature data from 30 streamgages across CONUS and surrogate models of streamflow depletion to analyse potential stream temperature impacts at each site. We compared two different stream temperature modelling approaches: (i) a process-based energy balance model and (ii) statistical regression models based on air temperature and stream discharge. We calculated a suite of thermal signatures under depleted and non-depleted conditions for each stream and found that maximum annual 7-day temperature and annual temperature range are potentially the most sensitive to streamflow depletion, with potential changes of at least 2°C at > 70% of the sites when using the process-based model. We also found that the regression-based models predicted much less sensitivity of stream temperature to streamflow depletion than the process-based model. This work provides an initial evaluation and sensitivity analysis of the potential impacts of streamflow depletion on stream temperature. We demonstrate that stream temperature may be most sensitive to pumping in streams with a high proportion of flow sourced from relatively cold groundwater inputs, and that regression-based stream temperature models may underpredict stream temperature changes caused by streamflow depletion.

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USGS2026

Groundwater drought in the United States: Spatial and temporal variability

Many communities and ecosystems in the United States that are dependent on groundwater are potentially adversely affected by groundwater drought. We computed yearly groundwater-drought metrics and mean groundwater levels at well locations across the conterminous United States (CONUS), using data from wells and remotely sensed and modeled Gravity Recovery and Climate Experiment Drought Monitor Data Assimilation (GRACE-DADM). We also modeled the probability of low or high human impact at each well location. The spatial distribution of groundwater-drought duration and severity from 2001 to 2020 for 1,510 wells shows longer maximum duration and higher maximum severity events in drier regions like the Southwest than in wetter regions like the Northeast. Based on 613 wells in CONUS from 1981 to 2020, there are many significant decreases in drought duration and severity in the Northeast and many significant increases in annual-mean groundwater levels. In contrast, there are many significant increases in drought metrics and decreases in mean water levels in parts of the Southeast. There are major differences in trends from 2001 to 2020 between well-based and GRACE-DADM-based groundwater metrics in some CONUS regions and a very low correlation between trends at individual locations across CONUS. A potential reason for this disparity is the low GRACE-DADM resolution (∼12 km) and the potential for a large amount of groundwater variation at the local scale. Also, GRACE-DADM represents shallow, unconfined aquifers which may not match the screened interval of the monitoring wells we evaluated. Large spatial gaps in long-term, high frequency, and quality-assured groundwater-well monitoring data present a challenge for understanding groundwater-drought variability across CONUS. Remote sensing tools such as GRACE can help but cannot fully replace well monitoring, as highlighted by our study results. Substantially more long-term monitoring wells would more accurately represent groundwater-drought trends and spatial variability across CONUS, particularly in western regions.

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USGS2026

Are mobile device location data a substitute for travel cost surveys?

Mobile device location data offer a low-cost alternative for measuring visitation to outdoor recreation sites and are known to correlate with official visitation counts. Less is known about whether these data can recover recreation demand and consumer surplus comparable to surveybased methods. We compare travel cost models estimated using mobile device and survey data for 17 U.S. National Park Service sites. Results are mixed. We examine the roles of aggregation and sampling bias and use LASSO regression to assess whether sample and site characteristics explain discrepancies.

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USGS2026

Aquatic reflectance derived from Sentinel-2 Multispectral Imager data for inland waters in the conterminous United States

Satellite-based earth observation is a robust tool for tracking change in ecosystems. While terrestrially focused applications of remote sensing have empowered wide adoption for research and management, remote sensing of inland aquatic ecosystems remains comparably nascent. This divergence, in part, stems from the lack of standardized, accessible, and near real-time remotely sensed surface reflectance, atmospherically corrected for aquatic environments. To date, surface reflectance products at national scales and with minimal latency are typically designed exclusively for terrestrial environments. Rectifying this situation can be accomplished by applying aquatic-focused atmospheric correction algorithms independent of those used for terrestrial ecosystems. As a first step to filling this data gap, we present the first national scale, dynamically updated, analysis-ready, aquatic reflectance dataset for inland water derived from Sentinel-2 for the conterminous United States.

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USGS2026

Identifying headwater streams across the conterminous United States

Headwater streams play critical roles in hydrologic and biogeochemical processes and functions, yet their spatial distribution and land cover context remain poorly understood at continental scales, and no dedicated geospatial dataset exists. Building from a high-resolution conterminous United States (CONUS) hydrography network dataset, we quantified the spatial extent, density, and upstream catchment characteristics of headwater stream segments across the CONUS. We identified approximately 8.4 million kilometers of headwater streams, finding that 77% of the total stream network consists of headwaters, nearly double the total length represented in prior estimates. Stream density varied fivefold across regions, from < 1 km·km −2 in arid basins to > 5 km·km −2 in humid, forested areas. Over 73% of the CONUS landmass drains from headwater streams. The majority of headwater stream length occurred in forested and cultivated catchments across the CONUS, while substantial regional differences were evident for headwater stream distribution in other land cover classes (for example, wetlands, urban areas, shrublands, and herbaceous-dominated catchments). The dedicated and novel geospatial dataset, HELiOS (HEadwater streams and Low-Order Systems) is introduced for management and research use. The HELiOS dataset provides the first continental-scale, high-resolution characterization of headwater streams, offering new insights and opportunities for hydrologic modeling, ecological assessments, and environmental policy.

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USGS2026

Characterizing the influence of remotely sensed wetland and lake water storage on discharge using LSTM models

Globally, many wetlands and lakes are at risk for further loss, which can amplify downstream consequences of flood and drought events. We derived remotely sensed based time series of surface water storage (SW storage ) to determine when and where accounting for SW storage dynamics improves predictions of river discharge. We trained four long short-term memory (LSTM) models, that differed in their inclusion of storage data and catchment characteristics, to simulate daily river discharge (2016–2023) for select watersheds across the conterminous United States. Adding SW storage to a meteorology-only or meteorology-and-catchment characteristics model improved upon model Nash-Sutcliffe efficiency (NSE) in 80.6% of the watersheds. Residuals during low-flow (Q70) events decreased by 47.6% when adding storage to meteorological data. Improvements were most consistent in ecoregions with a greater abundance of non-floodplain lakes and wetlands. This effort represents the first exploration to train a multi-watershed LSTM on landscape-scale remotely sensed time series of SW storage .

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USGS2026

Machine learning generated streamflow drought forecasts for the conterminous United States (CONUS): developing and evaluating an operational tool to enhance sub-seasonal to seasonal streamflow drought early warning for gaged locations

Forecasts of streamflow drought, when streamflow declines below typical levels, are notably less available than for floods or meteorological drought, despite widespread impacts. We apply machine learning (ML) models to forecast streamflow drought 1–13 weeks ahead at 3,219 streamgages across the conterminous United States. We applied two ML methods (Long short-term memory neural networks; Light Gradient-Boosting Machine) and two benchmark models (persistence; Autoregressive Integrated Moving Average) to predict weekly streamflow percentiles with independent models for each forecast horizon. ML models outperformed benchmarks in predicting continuous streamflow percentiles below 30%. ML models generally performed worse than persistence models for discrete classification (moderate, severe, extreme) but exceeded the benchmark models for drought onset/termination. Performance was better for less intense droughts and shorter horizons, with predictive power for 1–4 weeks for severe droughts (10% threshold). This work highlights challenges and opportunities to advance hydrological drought forecasting and supports a new experimental forecasting tool.

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USGS2026

A multidecadal metric of coastal wetland stability: Development of the Landsat-based UnVegetated-to-Vegetated Ratio (UVVR) version 2 spanning 1985-2022

The UnVegetated-to-Vegetated Ratio (UVVR) is a well-established metric of wetland condition, identifying stable wetlands with high vegetation cover and low vegetation cover wetlands prone to loss, informing research and management efforts in the coastal zone. In this study, we document the development and release of version 2 of UVVR (UVVR v2 ) for the coastal conterminous United States. UVVR v2 was derived from Landsat Collection-2 satellite imagery providing increased image consistency and geolocation accuracy. We describe several UVVR v2 updates including expanding the product record from 2014–2018 to 1985–2022 and improved calibration of spectral indices used to estimate fractional cover. We validated UVVR v2 and UVVR v1 against the MODIS Vegetation Continuous Field (VCF) products and demonstrate that UVVR v2 agrees well with VCF vegetation cover across the Atlantic, Gulf, and Pacific Coasts, with R 2 > 0.82 and root mean square errors (RMSEs) < 0.18 over five years. Relative to the UVVR v1 , UVVR v2 showed increases in R 2 > 0.29 and reductions in RMSEs > 0.12. Moving beyond metric development, we present several examples of UVVR v2 applications including multidecadal vegetation cover trend maps for various coastal wetland systems. Our findings demonstrate an increased ability to characterize wetland condition with Landsat Collection-2 imagery, and indicate that upcoming missions (e.g., Landsat Next) could result in further characterization improvements. Overall, UVVR v2 helps advance coastal wetlands monitoring and management efforts due to increased accuracy and longer period-of-record.

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USGS2025

A comprehensive geologic framework of the National Crustal Model for seismic hazard studies in the conterminous United States

A three-dimensional (3D) geologic framework has been developed for the conterminous United States (U.S.) as part of the U.S. Geological Survey National Crustal Model to enhance seismic hazard modeling. The geologic framework is created from geologic maps and multiple subsurface geologic unit boundaries including the base of the Miocene, Cenozoic, Phanerozoic, and the Mohorovičić discontinuity. Modifications are made to surficial geologic maps to remove discontinuities across state and country borders. The subsurface distribution of rock type and age is extrapolated from the surface, seeded with subsurface geologic information, and constrained by a map of basement geology. The framework provides the basis for estimates of subsurface seismic velocity and density that is needed to improve estimates of earthquake ground shaking and seismic hazard. The present framework greatly expands and updates a previously published 3D geologic framework of the western part of the U.S. that was itself a first-of-its-kind digital 3D portrayal of the nation.

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