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

USGS2021

Assessing the impact of drought on arsenic exposure from private domestic wells in the conterminous United States

This study assesses the potential impact of drought on arsenic exposure from private domestic wells by using a previously developed statistical model that predicts the probability of elevated arsenic concentrations (>10 μg per liter) in water from domestic wells located in the conterminous United States (CONUS). The application of the model to simulate drought conditions used systematically reduced precipitation and recharge values. The drought conditions resulted in higher probabilities of elevated arsenic throughout most of the CONUS. While the increase in the probability of elevated arsenic was generally less than 10% at any one location, when considered over the entire CONUS, the increase has considerable public health implications. The population exposed to elevated arsenic from domestic wells was estimated to increase from approximately 2.7 million to 4.1 million people during drought. The model was also run using total annual precipitation and groundwater recharge values from the year 2012 when drought existed over a large extent of the CONUS. This simulation provided a method for comparing the duration of drought to changes in the predicted probability of high arsenic in domestic wells. These results suggest that the probability of exposure to arsenic concentrations greater than 10 μg per liter increases with increasing duration of drought. These findings indicate that drought has a potentially adverse impact on the arsenic hazard from domestic wells throughout the CONUS.

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USGS2021

The river corridor’s evolving connectivity of lotic and lentic waters

River corridors supply a substantial proportion of the fresh water for societal and ecological needs. Individual functions of flowing (lotic) streams and rivers and ponded (lentic) waterbodies such as lakes and reservoirs are well-studied, but their collective functions are not as well understood. Here we bring together nationally consistent river corridor datasets to characterize the contributions of lotic and lentic features and to estimate changes over the past centuries. High-resolution datasets describing waterbodies across 10 million kilometers of the conterminous U.S. (CONUS) river network were classified by waterbody type and origin (historic vs. human-made or intensively managed), surface areal coverage, and degree of connectivity as estimated by a change in water residence timescale in river corridors. Four centuries of human disturbance drove large swings in river corridor makeup, with a transition toward more lotic systems caused by beaver extirpation and abandonment of waterwheel mill ponds by end of the nineteenth century. The twentieth century saw a vast expansion (49%) in river corridor areal coverage resulting from construction and management of small ponds and reservoirs for drinking water, hydropower, irrigation and livestock watering, and stormwater control. Water residence timescale in river corridors doubled or quadrupled over large areas, and more in specific locations, during the twentieth century as a result of the increased coverage of reservoirs and managed small ponds. Although reservoirs and lakes now dominate river corridor surface areas, we found that the growing number of small ponds impacts a greater proportion of network length through their influence on headwater streams where most water and chemical runoff enters the river corridor. We close with an agenda for integrated modeling of the physical, biogeochemical, and ecological drivers of river corridor functions, trajectories of change, and management opportunities.

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USGS2021

Determination of burn severity models ranging from regional to continental scales for the conterminous United States

Identifying meaningful measures of ecological change over large areas is dependent on the quantification of robust relationships between ecological metrics and remote sensing products. Over the past several decades, ground observations of wildfire and prescribed fire severity have been acquired across hundreds of wildland fires in the United States, primarily utilizing the Composite Burn Index (CBI) plot protocol. These observations have been coupled to spaceborne passive spectral reflectance indices (e.g. Landsat-derived variations of the Normalized Burn Ratio [NBR]) to produce regression models describing their relationship. Here we develop regression models by vegetation type for multiple vegetation classification systems representing a range of spatial scales, and a decision tree framework for evaluating these regression models. Our overall goals were to determine which scale of ecological classifications provided the best estimate of burn severity from Landsat data and how to choose the best regression model. We aggregated a total of 6280 CBI plots for 234 wildland fires that burned between 1994 and 2017 and produced Landsat-derived NBR and differenced NBR (dNBR) values for each plot. We then calculated best fit linear or higher order regression equations between CBI and NBR/dNBR for each landcover classification system from smallest to largest scale: LANDFIRE Biophysical Settings (BPS), National Vegetation Classification macrogroup (NVC) landcover classifications, Omernick III, II, and I ecoregions, LANDFIRE Fire Regime Groups (FRG), and the entire conterminous United States (CONUS) dataset. The CONUS regression model goodness of fit was moderate (R 2 = 0.55, P < 0.001) for dNBR and poor (R 2 = 0.30, P < 0.001) for NBR. Within landcover classifications, CBI was better fit by dNBR than NBR. Finer scale regional regression models including BPS (dNBR R 2 ¯ "> R2¯ = 0.56 and 0.00–0.83 R 2 range; NBR R 2 ¯ "> R(bar) 2 = 0.43 and 0.00–0.82 R 2 range) and NVC (dNBR R 2 ¯ "> R(bar) 2 = 0.55 and 0.15–0.78 R 2 range; NBR R 2 ¯ "> R(bar) 2 = 0.41 and 0.00–0.79 R 2 range) were on average the same or better than the CONUS models for dNBR and NBR, with the strongest fit models exhibiting R 2 ≥ 0.70, whereas larger scale regional models R 2 ¯ "> R(bar) 2 ranged from 0.28 to 0.5. However, variation in accuracy among landcover types indicate that dNBR and NBR regression models could be used to effectively estimate CBI for future fires in certain regions, while for other regions models may require additional field observations or alternative spectral transformations. Our decision tree schema can be used to help users determine which scale is likely to produce the most accurate results using our models. The CBI regression models developed here, paired with the decision tree, provide users with a simple method to estimate burn severity in units of CBI for any fire within CONUS with moderate to high levels of confidence and provide a template for further development of models with new data going forward.

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USGS2020

Water priorities for the Nation—U.S. Geological Survey Integrated Water Availability Assessments

The United States faces growing challenges to its water supply, infrastructure, and aquatic ecosystems because of population growth, climate change, floods and droughts, and aging water delivery systems. To help address these challenges, the U.S. Geological Survey (USGS) Water Resources Mission Area has established new strategic priorities that capitalize on the operational and scientific strengths of the USGS to address these complex societal issues. The USGS Integrated Water Availability Assessment Program within the Water Resources Mission Area will provide nationally consistent assessments of water available for human and ecological needs and identify factors that limit water availability. Integrated Water Availability Assessments will assess current conditions, long-term trends, factors responsible for current conditions and observed trends, and provide forecasts of future changes at national and regional scales.

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USGS2020

Reducing water scarcity by improving water productivity in the United States

Nearly one-sixth of U.S. river basins are unable to consistently meet societal water demands while also providing sufficient water for the environment. Water scarcity is expected to intensify and spread as populations increase, new water demands emerge, and climate changes. Improving water productivity by meeting realistic benchmarks for all water users could allow U.S. communities to expand economic activity and improve environmental flows. Here we utilize a spatially detailed database of water productivity to set realistic benchmarks for over 400 industries and products. We assess unrealized water savings achievable by each industry in each river basin within the conterminous U.S. by bringing all water users up to industry- and region-specific water productivity benchmarks. Some of the most water stressed areas throughout the U.S. West and South have the greatest potential for water savings, with around half of these water savings obtained by improving water productivity in the production of corn, cotton, and alfalfa. By incorporating benchmark-meeting water savings within a national hydrological model (WaSSI), we demonstrate that depletion of river flows across Western U.S. regions can be reduced on average by 6.2–23.2%, without reducing economic production. Lastly, we employ an environmentally extended input-output model to identify the U.S. industries and locations that can make the biggest impact by working with their suppliers to reduce water use 'upstream' in their supply chain. The agriculture and manufacturing sectors have the largest indirect water footprint due to their reliance on water-intensive inputs but these sectors also show the greatest capacity to reduce water consumption throughout their supply chains.

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USGS2020

Pyrrhotite distribution in the conterminous United States, 2020

In parts of Connecticut and Massachusetts, foundations of some homes are cracking and crumbling. Failing foundations can reduce the market value of a home and lifting a house to replace and repour a foundation is an expensive undertaking. In response, some homeowners are defaulting on their mortgages and abandoning their homes. The culprit is pyrrhotite, which occurs in construction aggregate (crushed stone) that was used as a filler in concrete. When pyrrhotite is naturally exposed to water and oxygen, it breaks down to produce sulfuric acid and secondary minerals, including gypsum, which have larger volumes than the pyrrhotite they replace. The expanded volume of the secondary minerals cracks and degrades concrete. Pyrrhotite occurs in rocks in many areas of the United States. To help assess the national risk of pyrrhotite in aggregate, the fiscal year 2019 appropriations bill for the U.S. Geological Survey’s (USGS) Mineral Resources Program allocated funds to develop a map showing the distribution of pyrrhotite across the United States. The purpose of this fact sheet is to (1) present a nationwide map that shows where pyrrhotite may occur in rocks in the United States, (2) describe and discuss the factors that control the presence and abundance of pyrrhotite in rocks, (3) provide information on geographic information system datasets that deliver more detailed information on these distributions, and (4) describe U.S. and international standards on aggregate that are designed to prevent failing concrete. While this map and fact sheet provide general information about the possible distribution of pyrrhotite in the United States, they are no substitute for site-specific characterization and quality control programs designed to ensure that aggregate used in concrete is of appropriate quality for its intended purpose.

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USGS2020

An enhanced hydrologic stream network based on the NHDPlus medium resolution dataset

The National Hydrography Dataset Plus, Version 2.1 (NHDPlusV2.1) is an attribute-rich digital stream network for the conterminous United States, serving as a foundational infrastructure for reporting hydrologic information at both regional and national scales. SPAtially Referenced Regressions On Watershed attributes (SPARROW) is a process-based statistical model that relies on a digital hydrologic network like NHDPlusV2.1 to establish spatial relations between quantities of monitored contaminant loads and contaminant sources, accounting for the physical characteristics along flow paths affecting contaminant transport. The U.S. Geological Survey National Water Quality Assessment project adopted and modified the medium-resolution NHDPlusV2.1 network for use as the primary framework supporting SPARROW modeling. This report describes the enhancements made to improve the routing capabilities and the value-added attributes of NHDPlusV2.1 to support modeling and other hydrologic analyses. These enhancements include corrections to inconsistencies in network/routing information, filling in missing attribute values of associated characteristics, accounting of water use affecting flow, new variables useful for interpreting network data, revised flowline attributes such as slope and flow, and incorporation of ancillary spatial data into the network. The resulting dataset containing the enhancements to the network is named E2NHDPlusV2_US. Although the enhancements described in the report were developed for use in SPARROW modeling, the enhancements are expected to be useful for a wide variety of hydrologic studies within the United States.

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USGS2020

Low streamflow trends at human-impacted and reference basins in the United States

We present a continent-scale exploration of trends in annual 7-day low streamflows at 2482 U.S. Geological Survey streamgages across the conterminous United States over the past 100, 75, and 50 years (1916–2015, 1941–2015 and 1966–2015). We used basin characteristics to identify subsets of study basins representative of reference basins with streamflow relatively free from human effects (n = 259), and predominantly agricultural basins (n = 78), regulated basins (n = 220), and urban basins (n = 121). Trend significance was computed using the Mann-Kendall test considering short- and long-term persistence. Lag-one autocorrelation tests of detrended 7-day low streamflows for all gage classes show that time-series independence is not an appropriate assumption for annual low streamflow data at many basins. Among all study gages, upward trends (wetter conditions) in 7-day low streamflows outnumbered downward trends (drier conditions) approximately 2–1 for the 75- and 100-year trend periods—50-year trends indicated roughly equal numbers of increases and decreases. Increases in 7-day low streamflow were consistently observed for all time periods throughout much of the northeastern quadrant of the conterminous U.S. including western New England and the Mid-Atlantic, the southeastern Great Lakes basin, northern Ohio River basin, and the Upper Mississippi River and eastern Missouri River basins. Decreases in 7-day low streamflow were consistently observed for all time periods at many gages in the southeastern U.S. and in the northwestern U.S. in much of Idaho and northwestern Washington. Overall, we observed greater percentages of statistically significant trends at gages with human-induced influences than at reference gages. Low-flow trends at agricultural gages were regionally consistent with trends at reference gages. Regulated basins had many statistically significant upward trends for all three time periods tested, which may be attributed in part to substantial increases in dam-related storage prior to 1970. Urban gages had the greatest percentage of significant decreases in 7-day low flows compared to all other gage classes even though most urban gages saw upward trends in mean annual flows. Urban gages also had the greatest percentage of significant increases in low flows second only to regulated gages, highlighting that urban development can increase or decrease low streamflows depending on the basin-specific development.

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USGS2020

Progress toward a preliminary karst depression density map for the conterminous United States

Most methods for the assessment of sinkhole hazard susceptibility are predicated upon knowledge of pre-existing closed depressions in karst areas. In the United States (U.S.), inventories of existing karst depressions are piecemeal, and are often obtained through inconsistent methodologies applied at the state or county level and at various scales. Here, we present a first attempt at defining a karst closed depression inventory across the conterminous U.S. using a common methodology. Automated algorithms for extraction of closed depressions from 1/3 arc-second (approximately 10 m resolution) National Elevation Dataset (NED) were run on the U.S. Geological Survey (USGS) “Yeti” high-performance computing cluster. The full NED was first conditioned to reduce the creation of artificial closed depressions by breaching digital dams at road and stream crossings, using the flowlines and transportation route vectors from the USGS National Map. The resulting depressions were selected according to location within geologic units having the potential for karst, and screened for occurrence in areas of developed land, open water and wetlands, and areas of glacial and alluvial sediment cover. The results were used as the input to create a nationwide depression density map. Our results were compared with karst depression density maps for diverse karst regions within states that have existing closed depression inventories. The individual state-scale maps compared favorably to the results obtained from the method applied universally across the nation and illustrated regional sinkhole hotspots in known areas of well-developed karst. Limitations of the automated method includes false positive depressions resulting from artifacts generated during the computer processing of the elevation models, and inclusion of depressions resulting from non-karst geomorphic processes. More thorough examination of the screening criteria for depressions is required.

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USGS2019

Severity and extent of alterations to natural streamflow regimes based on hydrologic metrics in the conterminous United States, 1980–2014

Alteration of the natural streamflow regime by land and water management, such as land-cover change and dams, is associated with aquatic ecosystem degradation. The severity and geographic extent of streamflow alteration at regional and national scales, however, remain largely unquantified. The primary goal of this study is to characterize the severity and extent of alterations to natural streamflow regimes for 1980–2014 based on hydrologic metrics at 3,355 U.S. Geological Survey streamgages in the conterminous United States. Twelve hydrologic metrics with known relevance to aquatic ecosystem health were used to characterize the streamflow regime. Alterations to the 12 hydrologic metrics were quantified by taking ratios of the metrics calculated from observed daily streamflow records divided by the same metrics predicted for natural conditions by random forest statistical models. Some level of streamflow alteration (diminishment or inflation of hydrologic metrics) compared to natural conditions was indicated at about 80 percent of the assessed streamgages across the conterminous United States. The severity of alteration differed among ecoregions because of differences in dominant land and water management practices. Finally, when compared over the period 1980–2014, climate variability generally played a minor role in the alteration of streamflows across the United States when compared to the effects of land and water management.

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USGS2019

Tritium as an indicator of modern, mixed, and premodern groundwater age

Categorical classification of groundwater age is often used for the assessment and understanding of groundwater resources. This report presents a tritium-based age classification system for the conterminous United States based on tritium ( 3 H) thresholds that vary in space and time: modern (recharged in 1953 or later), if the measured value is larger than an upper threshold; premodern (recharged prior to 1953) if the measured value is smaller than a lower threshold; or mixed if the measured value is between the two thresholds. Inclusion of spatially varying thresholds, rather than a single threshold, accounts for the observed systematic variation in 3 H deposition across the United States. Inclusion of time-varying thresholds, rather than a single threshold, accounts for the date of sampling given the radioactive decay of 3 H. The efficacy of the tritium-based age classification system was evaluated at national and regional scales. The system was evaluated at a national scale by classifying samples from 1,788 public-supply wells distributed across 19 principal aquifers and comparing those results with expectations based on hydrogeologic principles. The regional-scale data are from five paired networks of shallow and deep wells (287 wells). As expected, modern groundwater is more prevalent in shallow wells than in deeper wells, in fractured-rock and carbonate aquifers as compared to clastic aquifers, in unconfined areas as compared to confined areas, and in humid climates as compared to arid climates. The results from a tritium-based age classification system compared favorably with the results of 14 previous studies of groundwater ages that used different age tracers and analytical methods. The wells and samples from the Cambrian-Ordovician aquifer that had been analyzed using a more complex multi-tracer analysis were also analyzed using the tritium-based age classification system, and there was a close match between the two methods. The results from these various studies suggest that the tritium-based age classification system may be informative as a screening tool prior to selecting more expensive and complex age-dating tracers and methods, or to provide an explanatory variable for other water-quality data where more complex methods or tracers are not available. This work improves on previous groundwater age classification using 3 H by developing methods that (1) determine 3 H thresholds for groundwater recharged in 1953 or later that minimize the misclassification of modern samples as mixed; (2) determine a pre-1953 threshold to estimate premodern background concentrations; and (3) add a mixed category to classify samples that are clearly neither entirely modern nor entirely premodern. As with any tritium-based approach, it can fail when the 3 H record in precipitation does not accurately reflect the record of 3 H in recharge

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USGS2019

Evaluating the temperature difference parameter in the SSEBop model with satellite observed land surface temperature data

The Operational Simplified Surface Energy Balance (SSEBop) model uses the principle of satellite psychrometry to produce spatially explicit actual evapotranspiration (ETa) with remotely sensed and weather data. The temperature difference ( dT ) in the model is a predefined parameter quantifying the difference between surface temperature at bare soil and air temperature at canopy level. Because dT is derived from the average-sky net radiation based primarily on climate data, validation of the dT estimation is critical for assuring a high-quality ETa product. We used the Moderate Resolution Imaging Spectroradiometer (MODIS) data to evaluate the SSEBop dT estimation for the conterminous United States. MODIS data (2008–2017) were processed to compute the 10-year average land surface temperature (LST) and normalized difference vegetation index (NDVI) at 1 km resolution and 8-day interval. The observed dT ( dT o ) was computed from the LST difference between hot (NDVI < 0.25) and cold (NDVI > 0.7) pixels within each 2° × 2° sampling block. There were enough hot and cold pixels within each block to create dT o timeseries in the West Coast and South-Central regions. The comparison of dT o and modeled dT ( dT m ) showed high agreement, with a bias of 0.8 K and a correlation coefficient of 0.88 on average. This study concludes that the dT m estimation from the SSEBop model is reliable, which further assures the accuracy of the ETa estimation.

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USGS2019

Estimates of long-term mean daily streamflow and annual nutrient and suspended-sediment loads considered for use in regional SPARROW models of the Conterminous United States, 2012 base year

Streamflow, nutrient, and sediment concentration data needed to estimate long-term mean daily streamflow and annual constituent loads were compiled from Federal, State, Tribal, and regional agencies, universities, and nongovernmental organizations. The streamflow and loads are used to develop Spatially Referenced Regressions on Watershed Attributes (SPARROW) models. SPARROW models help describe the distribution, sources, and transport of streamflow, nutrients, and sediment in streams throughout five regions of the conterminous United States. After the data were screened, approximately 5,200 streamflow, 3,000 sediment, and 3,300 nutrient sites, sampled by 137 agencies and organizations were identified as having suitable data for calculating the long-term mean daily streamflow and annual nutrient and sediment loads required for SPARROW model estimation. These sites are representative of a wide range in terms of watershed size, contaminant source types, and land-use and other important watershed characteristics. The methods used to estimate long-term mean annual loads include the Beale ratio estimator and Fluxmaster regression method with Kalman smoothing.

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USGS2019

The U. S. Geological Survey National Hydrologic Model infrastructure: Rationale, description, and application of a watershed-scale model for the conterminous United States

The ability to effectively manage water resources to meet present and future human and environmental needs is essential. Such an ability necessitates a comprehensive understanding of hydrologic processes that affect streamflow at a watershed scale. In the United States, water-resources management at scales ranging from local to national can benefit from a nationally consistent, process-based watershed modeling capability to provide the requisite understanding. The National Hydrologic Model (NHM) infrastructure, which was developed by the U.S. Geological Survey to support coordinated, comprehensive, and consistent hydrologic modeling at multiple scales for the conterminous United States, provides this essential capability. NHM-based applications provide information to enable more effective water-resources planning and management, fill knowledge gaps in ungaged areas, and support basic scientific inquiry. In the future, as process algorithms and data sets improve, the NHM infrastructure will continue to evolve to better support the nation's water-resources research and management needs.

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USGS2018

A new generation of the United States National Land Cover Database: Requirements, research priorities, design, and implementation strategies

The U.S. Geological Survey (USGS), in partnership with several federal agencies, has developed and released four National Land Cover Database (NLCD) products over the past two decades: NLCD 1992, 2001, 2006, and 2011. These products provide spatially explicit and reliable information on the Nation’s land cover and land cover change. To continue the legacy of NLCD and further establish a long-term monitoring capability for the Nation’s land resources, the USGS has designed a new generation of NLCD products named NLCD 2016. The NLCD 2016 design aims to provide innovative, consistent, and robust methodologies for production of a multi-temporal land cover and land cover change database from 2001 to 2016 at 2–3-year intervals. Comprehensive research was conducted and resulted in developed strategies for NLCD 2016: a streamlined process for assembling and preprocessing Landsat imagery and geospatial ancillary datasets; a multi-source integrated training data development and decision-tree based land cover classifications; a temporally, spectrally, and spatially integrated land cover change analysis strategy; a hierarchical theme-based post-classification and integration protocol for generating land cover and change products; a continuous fields biophysical parameters modeling method; and an automated scripted operational system for the NLCD 2016 production. The performance of the developed strategies and methods were tested in twenty World Reference System-2 path/row throughout the conterminous U.S. An overall agreement ranging from 71% to 97% between land cover classification and reference data was achieved for all tested area and all years. Results from this study confirm the robustness of this comprehensive and highly automated procedure for NLCD 2016 operational mapping.

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USGS2016

Regional differences in upland forest to developed (urban) land cover conversions in the conterminous U.S., 1973–2011

In this U.S. Geological Survey study of forest land cover across the conterminous U.S. (CONUS), specific proportions and rates of forest conversion to developed (urban) land were assessed on an ecoregional basis. The study period was divided into six time intervals between 1973 and 2011. Forest land cover was the source of 40% or more of the new urban land in 35 of the 84 ecoregions located within the CONUS. In 11 of these ecoregions this threshold exceeded in every time interval. When the percent of change, forest to urban, was compared to the percent of forest in each ecoregion, 58 ecoregions had a greater percent of change and, in six of those, change occurred in every time interval. Annual rates of forest to urban land cover change of 0.2% or higher occurred in 12 ecoregions at least once and in one ecoregion in all intervals. There were three ecoregions where the above conditions were met for nearly every time interval. Even though only a small number of the ecoregions were heavily impacted by forest loss to urban development within the CONUS, the ecosystem services provided by undeveloped forest land cover need to be quantified more completely to better inform future regional land management.

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USGS2015

Completion of the 2011 National Land Cover Database for the conterminous United States – Representing a decade of land cover change information

The National Land Cover Database (NLCD) provides nationwide data on land cover and land cover change at the native 30-m spatial resolution of the Landsat Thematic Mapper (TM). The database is designed to provide five-year cyclical updating of United States land cover and associated changes. The recent release of NLCD 2011 products now represents a decade of consistently produced land cover and impervious surface for the Nation across three periods: 2001, 2006, and 2011 (Homer et al., 2007; Fry et al., 2011). Tree canopy cover has also been produced for 2011 (Coluston et al., 2012; Coluston et al., 2013). With the release of NLCD 2011, the database provides the ability to move beyond simple change detection to monitoring and trend assessments. NLCD 2011 represents the latest evolution of NLCD products, continuing its focus on consistency, production, efficiency, and product accuracy. NLCD products are designed for widespread application in biology, climate, education, land management, hydrology, environmental planning, risk and disease analysis, telecommunications and visualization, and are available for no cost at http://www.mrlc.gov. NLCD is produced by a Federal agency consortium called the Multi-Resolution Land Characteristics Consortium (MRLC) (Wickham et al., 2014). In the consortium arrangement, the U.S. Geological Survey (USGS) leads NLCD land cover and imperviousness production for the bulk of the Nation; the National Oceanic and Atmospheric Administration (NOAA) completes NLCD land cover for the conterminous U.S. (CONUS) coastal zones; and the U.S. Forest Service (USFS) designs and produces the NLCD tree canopy cover product. Other MRLC partners collaborate through resource or data contribution to ensure NLCD products meet their respective program needs (Wickham et al., 2014).

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USGS2014

Geochemical and mineralogical maps for soils of the conterminous United States

The U.S. Geological Survey began sampling in 2007 for a low-density (1 site per 1,600 square kilometers, 4,857 sites) geochemical and mineralogical survey of soils in the conterminous United States as part of the North American Soil Geochemical Landscapes Project. The sampling protocol for the national-scale survey included, at each site, a sample from a depth of 0 to 5 centimeters, a composite of the soil A horizon, and a deeper sample from the soil C horizon or, if the top of the C horizon was at a depth greater than 1 meter, a sample from a depth of approximately 80–100 centimeters. The <2-millimeter fraction of each sample was analyzed for a suite of 45 major and trace elements by methods that yield the total or near-total elemental content. The major mineralogical components in the samples from the soil A and C horizons were determined by a quantitative X-ray diffraction method using Rietveld refinement. Sampling in the conterminous United States was completed in 2010, with chemical and mineralogical analyses completed in May 2013. The resulting data set provides an estimate of the abundance and spatial distribution of chemical elements and minerals in soils of the conterminous United States and represents a baseline for soil geochemistry and mineralogy against which future changes may be recognized and quantified. This report releases geochemical and mineralogical maps along with a histogram, boxplot, and empirical cumulative distribution function plot for each element or mineral.

Conterminous United States↗