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USGS2015

Conflict minerals from the Democratic Republic of the Congo—Gold supply chain

The U.S. Geological Survey (USGS) analyzes mineral and metal supply chains to identify and describe major components of material flows from ore extraction, through intermediate forms, to a final product. Supply chain analyses may be used to identify risks to the United States associated with the supply of critical and strategic minerals and metals and to provide greater supply chain transparency so that policymakers have the fact-based information needed to formulate public policy. This fact sheet focuses on the gold supply chain. The USGS National Minerals Information Center (NMIC) has been asked by governmental and non-governmental organizations to provide information about tantalum, tin, tungsten, and gold (collectively known as “3TG minerals” ) processing facilities worldwide in response to U.S. legislation aimed at identifying and removing the supply chain links associated with the trade of these metals and minerals among armed groups in the Democratic Republic of the Congo (DRC) and adjacent countries. Post-beneficiation processing plants (generally called smelters and refineries) for tantalum, tin, and tungsten (3T) mineral ores and concentrates were identified by company and industry association representatives as being the link in the 3T mineral supply chain through which these minerals can be traced to their source of origin (mine). Tungsten processing plants were the subject of the first fact sheet in a series of USGS reports about 3TG minerals, which was published by the NMIC in August 2014 (Bermúdez-Lugo, 2014). Background information about historical conditions and the voluntary due diligence of multinational stakeholders for minerals from conflict-affected and high-risk areas is presented in the tungsten fact sheet. The current fact sheet, the fourth and last in the series about 3TG minerals, focuses on the gold supply chain. Processing of the 3T mineral concentrates requires substantial infrastructure and capital and generally is done at relatively few specialized facilities that are not located at the mine site; primary and secondary processors typically are at separate locations. Gold, however, can easily be processed into semi-refined products at or near the mine site and has a high unit value in any form, which allows it to be readily exported through undocumented channels, making it more difficult to track to the mine or region of origin. To put this in perspective, 30 kilograms (66 pounds) of 83 percent pure gold (20 carat) would form a cube measuring 12 centimeters per side (about the size of a small tissue box) and, at a price of $1,200 per ounce, would be worth nearly $1 million. By contrast, the equivalent value of tungsten concentrates would weigh about 45 metric tons (t) (100,000 pounds). Once conflict sourced gold has been combined with gold from other mines and scrap at a refiner, there is no feasible way to distinguish the source of the gold. Thus, once the gold leaves the immediate area of production, it is nearly indistinguishable from gold products mined in other areas.

Fact Sheet↗

USGS2012

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Zarkashan mineral district in Afghanistan: Chapter G in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Zarkashan mineral district, which has copper and gold deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2006,2007, 2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. Therefore, it was necessary to (1) register the 10-m AVNIR multispectral imagery to a well-controlled Landsat image base, (2) mosaic the individual multispectral images into a single image of the entire area of interest, (3) register each panchromatic image to the registered multispectral image base, and (4) mosaic the individual panchromatic images into a single image of the entire area of interest. The two image-registration steps were facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band’s picture element based on the digital values of all picture elements within a 315-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area’s local zone (42 for Zarkashan) and the WGS84 datum. The final image mosaics were subdivided into two overlapping tiles or quadrants because of the large size of the target area. The two image tiles (or quadrants) for the Zarkashan area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image. Within the Zarkashan study area, three subareas were designated for detailed field investigations (that is, the Mine Area, Bolo Gold Prospect, and Luman-Tamaki Gold Prospect subareas); these subareas were extracted from the area’s image mosaic and are provided as separate embedded geotiff images.

Zarkashan Mineral District↗

USGS2019

Hurricane Sandy impacts on coastal wetland resilience

The goal of this research was to evaluate the impacts of Hurricane Sandy on surface elevation trends in estuarine marshes located across the northeast region of the United States from Virginia to Maine using data from an opportunistic (in other words, not strategic) and collaborative network (from here on, an opportunistic network) of surface elevation table-marker horizon (SET-MH) stations. First, we built a data-base of metadata for 965 individual stations from 96 unique geographical locations that included the location, geomorphic setting, and wetland type for each SET-MH station. The dominant estuarine settings included in the analyses were back-barrier lagoonal marshes and emergent marshes along embayments and tidal tributaries. We then calculated prestorm elevation trends to compare to poststorm elevation measurements to determine the storm impact on each station trend. We hypothesized that the effect of Hurricane Sandy on marsh elevation trends would differ by position relative to landfall (right or left) and distance from landfall in southern New Jersey, as both of these variables influence the presence or absence of storm surge as a result of the physical characteristics of tropical cyclones (in other words, strongest winds typically occur to the right of landfall). Storm surge was spatially less extensive and less deep (~1 meter [m]) in marshes located to the left (in other words, south) of landfall compared to marshes located to the right (in other words, north) of landfall where storm surge covered a larger area and was deeper (3–4 m). About 63 percent of 223 eligible stations had a poststorm trend that was similar to the prestorm trend (in other words, less than ±5 millimeters [mm]), indicating little storm impact on elevation trends at those sites. The remaining 37 percent of stations exhibited significant poststorm deviations from the prestorm trend (in other words, greater than ±5 mm). Of these, stations located to the left of landfall had a significant and greater deviation in their elevation trend, and the deviation was more likely to be positive (elevation gain) compared to marshes located to the right of landfall, which had a significant deviation in their elevation trend that was more likely to be negative (elevation loss). This finding is directly related to storm surge impacts on marsh sediment deposition, where deep storm surge (3–4 m) results in sediment deposition in habitats inland of coastal marshes but less so in the marshes themselves. Substrate compaction by the storm surge over-burden may have contributed to elevation loss, but this was not measured because sufficient marker horizon data were not available for analysis. In contrast, to the left of landfall the wind-driven flooding of sediment laden water pushed into the headwaters of rivers and small bays with an ~1 m surge, and resulted in more prevalent sediment deposition on the marsh surfaces and elevation gain. In general, the findings support previous research showing that the physical characteristics of the storm (for example, wind speed, storm surge height, impact angle of landfall) combined with the local wetland conditions (for example, marsh productivity, groundwater level, tide height) are important factors determining a storm’s impact on soil elevation, and that the soil elevation response can vary widely among multiple wetland sites impacted by the same storm and among different storms for the same wetland site. The final objective of this project was to create a framework using metadata from the opportunistic network of SET-MH stations that could be used to develop a strategic monitoring network designed to address specific climate change impacts and related phenomena identified by land managers and stakeholders. We evaluated the spatial distribution and density of SET-MH stations in relation to geographic coverage, marsh setting, availability of public land, and historical storm surge footprints and hurricane return intervals in order to identify gaps in our understanding of risk and our ability to assess it. Analyses revealed that the general geographic coverage of SET-MH stations is limited given the low percentage of marsh patches with stations, low density of stations, the clumped distribution of stations, and the often limited and uneven distribution of stations in wetlands with a high historical frequency of hurricane strikes and storm surge impacts. These findings can be used by managers and planners to inform the creation of a strategic monitoring network that can, in turn, inform management and adaptation plans for coastal resources in the region. Final plan designs will need to consider financial and infrastructural support required for station maintenance, as well as data collection and management over the long term.

Open-File Report↗

USGS1996

Documentation of programs used to determine a wetlands hydroperiod from model-simulated water-surface elevations

A technique has been developed to determine a wetlands hydroperiod by comparing simulated water levels from a ground-water flow model and land- surface elevation data through a geographic information system. The simulated water levels are compared with the land-surface elevation data to determine the height of the water surface above or below land surface for the area of interest. Finally, the hydroperiod is determined for established time periods using criteria specified by the user. The program application requires the use of geographic information system software (ARC/INFO), including the TIN and GRID subsystems of the software. The application consists of an ANSI compatible C program to translate ground- water data output from the U.S. Geological Survey modular three-dimensional, finite-difference, ground-water flow model (MODFLOW) into a format that can be used as input for the geographic information system programs (AML's). The application uses ARC/INFO AML programs and ARC/INFO menu interface programs to create digital spatial data layers of the land surface and water surface and to determine the hydroperiod. The technique can be used to evaluate and manage wetlands hydrology.

Open-File Report↗

USGS2018

Variations on a method for evaluating decadal-scale changes in the groundwater quality of two GAMA coastal study units 2004–14, California GAMA Priority Basin Project

Decadal changes in groundwater quality in two study units on the north-central California coast were evaluated by the Priority Basin Project (PBP) of the Groundwater Ambient Monitoring and Assessment (GAMA) Program. Groundwater samples collected from wells during 2004–05 were compared on a pair-wise basis to samples collected from the same wells during 2014. The data set consisted of paired-samples from 50 public supply wells in 2 GAMA-PBP study units (25 wells each in the North San Francisco Bay and the Monterey Bay and Salinas Valley Basins), with analytical results for 160 water-quality constituents. Statistical analysis was done on grouped results for the 59 constituents that were detected in at least 10 percent of the samples during either sampling period to evaluate decadal-scale change by a step-trend analysis. The data for both of the sampling periods were processed three different ways, resulting in three variations of the paired results to be submitted for statistical analyses. The first evaluation method variation processed data only to facilitate comparison of data when one or both of the results was a non-detection. The second and third variations applied the additional requirement that differences between initial and decadal-sample results exceed a defined threshold to prevent small differences from supporting the conclusion of a step trend. One method for setting the difference threshold between initial-sampling and resampling results is based on criteria used by the GAMA-PBP to determine whether or not replicate results are acceptable. The other difference-threshold-setting method uses a calculated confidence interval around each result based on demonstrated analytical variability for the constituents during each sampling period. Finally, constituents for which decadal-scale changes were statistically significant were identified using the Wilcoxon-Pratt signed-rank test on each of the three evaluation method variations. Step trends were identified by at least 1 of the 3 method variations for 33 constituents. After considering other factors, however, such as water-quality context and the results of quality-control samples, it was concluded that decadal changes were meaningful for 14 constituents in at least 1 of the 2 study units. Constituents for which step trends indicated meaningful increases were dissolved oxygen, total nitrogen, nitrate, orthophosphate, calcium, chloride, sulfate, iron, and lithium. Constituents for which step trends indicated meaningful decreases were temperature, arsenic, lead, the isotopic ratio of carbon-13, and tritium.

California↗

USGS2012

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Dusar-Shaida mineral district in Afghanistan: Chapter I in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Dusar-Shaida mineral district, which has copper and tin deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. For this particular area, PRISM image orthorectification was performed by the Alaska Satellite Facility, applying its photogrammetric software to PRISM stereo images with vertical control points obtained from the digital elevation database produced by the Shuttle Radar Topography Mission (Farr and others, 2007) and horizontal adjustments based on a controlled Landsat image base (Davis, 2006). The 10-m AVNIR multispectral imagery was then coregistered to the orthorectified PRISM images and individual multispectral and panchromatic images were mosaicked into single images of the entire area of interest. The image coregistration was facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band’ picture element based on the digital values of all picture elements within a 315-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area’ local zone (41 for Dusar-Shaida) and the WGS84 datum. The final image mosaics were subdivided into eight overlapping tiles or quadrants because of the large size of the target area. The eight image tiles (or quadrants) for the Dusar-Shaida area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image. Within the Dusar-Shaida study area, three subareas were designated for detailed field investigations (that is, the Dahana-Misgaran, Kaftar VMS, and Shaida subareas); these subareas were extracted from the area’ image mosaic and are provided as separate embedded geotiff images.

Farah;Herat↗

USGS2011

Improvement in precipitation-runoff model simulations by recalibration with basin-specific data, and subsequent model applications, Onondaga Lake Basin, Onondaga County, New York

Water-resource managers in Onondaga County, New York, are faced with the challenge of improving the water quality of Onondaga Lake, which has the distinction of being one of the most contaminated lakes in the United States. To assist in this endeavor, during 2003-07 the U.S. Geological Survey (USGS), in cooperation with the Onondaga Lake Partnership, developed a precipitation-runoff model of the 285-square-mile Onondaga Lake Basin with the computer program Hydrological Simulation Program-Fortran (HSPF). The model was intended to provide a tool whereby the processes responsible for the generation of loads of sediment and nutrients that are transported to Onondaga Lake could be better understood. This objective was only partly attained because data for calibration of the model were available from monitoring sites only at or near the mouths of the major tributaries to Onondaga Lake; no calibration data from headwater subbasins, where the loads originated, were available. To address this limitation and thereby decrease the uncertainty in the simulated results that were associated with headwater processes, the USGS conducted a 3-year (2005-08) basinwide study to assess the quality of surface water in the Onondaga Lake Basin. The study quantified the relative contributions of nonpoint sources associated with the major land uses and land covers in the basin and also monitored known sources and presumed sinks of sediment and nutrient loads, which previously had not been evaluated. The use of the newly acquired data to recalibrate the HSPF model resulted in improvements in the simulation of processes in the headwater subbasins, including suspended-sediment, orthophosphate, and phosphorus generation and transport. Simulation of streamflows in small subbasins was improved by adjusting model parameter values to match base flows, storm peaks, and storm recessions more precisely than had been done with the original model. Simulated recessional and low flows were either increased or decreased as appropriate for a given stream, and simulated peak flows generally were lowered in the revised model. The use of suspended-sediment concentrations rather than concentrations of the surrogate constituent, total suspended solids, resulted in increases in the simulated low-flow sediment concentrations and, in most cases, decreases in the simulated peak-flow sediment concentrations. Simulated orthophosphate concentrations in base flows generally increased but decreased for peak flows in selected headwater subbasins in the revised model. Compared with the original model, phosphorus concentrations simulated by the revised model were comparable in forested subbasins, generally decreased in developed and wetland-dominated subbasins, and increased in agricultural subbasins. A final revision to the model was made by the addition of the simulation of chloride (salt) concentrations in the Onondaga Creek Basin to help water-resource managers better understand the relative contributions of salt from multiple sources in this particular tributary. The calibrated revised model was used to (1) compute loading rates for the various land types that were simulated in the model, (2) conduct a watershed-management analysis that estimated the portion of the total load that was likely to be transported to Onondaga Lake from each of the modeled subbasins, (3) compute and assess chloride loads to Onondaga Lake from the Onondaga Creek Basin, and (4) simulate precolonization (forested) conditions in the basin to estimate the probable minimum phosphorus loads to the lake.

Onondaga, New York↗

USGS2014

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Ghazni1 mineral district in Afghanistan

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Ghazni1 mineral district, which has spectral reflectance anomalies indicative of clay, aluminum, gold, silver, mercury, and sulfur deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA, 2008, 2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. Therefore, it was necessary to (1) register the 10-m AVNIR multispectral imagery to a well-controlled Landsat image base, (2) mosaic the individual multispectral images into a single image of the entire area of interest, (3) register each panchromatic image to the registered multispectral image base, and (4) mosaic the individual panchromatic images into a single image of the entire area of interest. The two image-registration steps were facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band's picture element based on the digital values of all picture elements within a 500-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area's local zone (42 for Ghazni1) and the WGS84 datum. The images for the Ghazni1 area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image.

Ghazni1 Mineral District↗

USGS2014

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Ghazni2 mineral district in Afghanistan

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Ghazni2 mineral district, which has spectral reflectance anomalies indicative of gold, mercury, and sulfur deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA, 2008, 2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. Therefore, it was necessary to (1) register the 10-m AVNIR multispectral imagery to a well-controlled Landsat image base, (2) mosaic the individual multispectral images into a single image of the entire area of interest, (3) register each panchromatic image to the registered multispectral image base, and (4) mosaic the individual panchromatic images into a single image of the entire area of interest. The two image-registration steps were facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band's picture element based on the digital values of all picture elements within a 500-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area's local zone (42 for Ghazni2) and the WGS84 datum. The images for the Ghazni2 area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image.

Ghazni2 Mineral District↗

USGS2013

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Ghunday-Achin mineral district in Afghanistan, in Davis, P.A, compiler, Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Ghunday-Achin mineral district, which has magnesite and talc deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2008,2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. For this particular area, PRISM image orthorectification was performed by the Alaska Satellite Facility, applying its photogrammetric software to PRISM stereo images with vertical control points obtained from the digital elevation database produced by the Shuttle Radar Topography Mission (Farr and others, 2007) and horizontal adjustments based on a controlled Landsat image base (Davis, 2006). The 10-m AVNIR multispectral imagery was then coregistered to the orthorectified PRISM images and individual multispectral and panchromatic images were mosaicked into single images of the entire area of interest. The image coregistration was facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band’s picture element based on the digital values of all picture elements within a 500-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area’s local zone (42 for Ghunday-Achin) and the WGS84 datum. The final image mosaics were subdivided into six overlapping tiles or quadrants because of the large size of the target area. The six image tiles (or quadrants) for the Ghunday-Achin area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image. Within the Ghunday-Achin study area, two subareas were designated for detailed field investigations (that is, the Achin-Magnesite and Ghunday-Mamahel subareas); these subareas were extracted from the area’s image mosaic and are provided as separate embedded geotiff images.

Data Series↗

USGS1990

The next big earthquake in the Bay Area may come sooner than you think—Are you prepared?

Many of us breathed a little easier after October 17, 1989. The Lorna Prieta earthquake, 7.1 on the Richter scale, meant that the big one, talked about for decades, had finally happened. And, bad as it was, we had survived. There are two things wrong with that. First, Lorna Prieta was not the big one. It was a moderately big one, certainly destructive to some parts of the Bay Area, but nowhere near the size of the great San Francisco earthquake of 1906. Second, having an earthquake like Lorna Prieta has little to do with the likelihood of having another one on a different fault, somewhere else in the area. The inevitability of a damaging earthquake still confronts everybody in the Bay Area, and we still risk substantial damage. A new study, released in July 1990 by the United States Geological Survey, says that there is a 67 percent chance of another earthquake the size of Lorna Prieta during the next 30 years and that the quake could strike at any time, including today. In other words, scientists think that a magnitude 7 or larger earthquake is now twice as likely to happen as not to happen. This is a substantial increase, since in 1988, scientists thought the chance for such an earthquake was 50 percent Gust as likely to occur as not to occur) within 30 years. The new report also says that the next one will most likely strike farther north than Lorna Prieta, somewhere between San Jose and Santa Rosa on either side of the Bay. The epicenter of the October 1989 quake was in a sparsely populated area. The next one, according to the study, will likely be centered in a more populated area. During the Lorna Prieta earthquake, shaking was so severe in the Santa Cruz Mountains that a van overturned, treetops snapped off, and many people were thrown to the ground. Because the next one is expected to strike closer to an urban area, it will cause much more damage. Fortunately, there is something we can do about it. By taking actions, such as those described in this booklet, we can drastically reduce the losses and we can make the Bay Area a safer place to live. Earthquake damage is particularly great in certain locations and in certain buildings. Most locations and most modem buildings are relatively safe. By identifying the greatest hazards, we can set priorities for using our limited resources most effectively to reduce them. The choice is ours.

General Interest Publication↗

USGS2012

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Kundalyan mineral district in Afghanistan: Chapter H in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Kundalyan mineral district, which has porphyry copper and gold deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. For this particular area, PRISM image orthorectification was performed by the Alaska Satellite Facility, applying its photogrammetric software to PRISM stereo images with vertical control points obtained from the digital elevation database produced by the Shuttle Radar Topography Mission (Farr and others, 2007) and horizontal adjustments based on a controlled Landsat image base (Davis, 2006). The 10-m AVNIR multispectral imagery was then coregistered to the orthorectified PRISM images and individual multispectral and panchromatic images were mosaicked into single images of the entire area of interest. The image coregistration was facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band’s picture element based on the digital values of all picture elements within a 500-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area’s local zone (42 for Kundalyan) and the WGS84 datum. The final image mosaics were subdivided into five overlapping tiles or quadrants because of the large size of the target area. The five image tiles (or quadrants) for the Kundalyan area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image. Within the Kundalyan study area, three subareas were designated for detailed field investigations (that is, the Baghawan-Garangh, Charsu-Ghumbad, and Kunag Skarn subareas); these subareas were extracted from the area’s image mosaic and are provided as separate embedded geotiff images.

Kundalyan Mineral District↗

USGS1994

National Water-Quality Assessment Program: the Northern New England Basins study unit

In 1991, the U.S. Geological Survey (USGS), U.S. Department of the Interior, began a full-scale National Water-Quality Assessment (NAWQA) program. The objectives of the NAWQA program are to describe the present and future water quality of large, representative parts of the United States's surface- and ground-water resources and to identify the primary natural and man-made factors that affect the quality of these resources. The final product of the program will be information that may be used by water-resource policy makers and managers at national, State, and local levels. The NAWQA program encompasses 60 study units. These units are delineated by hydrologic systems that include parts of most of the Nation's major river basins and aquifer systems. Study units range in size from 1,000 mi 2 (square miles) to more than 60,000 mi 2 and represent 60 to 70 percent of the Nation's water use and population served by public water supplies. The first group of 20 study-unit investigations began in 1991. A second group of 20 study-unit investigations began in 1994, which includes the Northern New England Basins study unit.

Maine;Massachusetts;New Hampshire↗

USGS1956

Uranium distribution in pseudowollastonite slag from a phosphorus furnace

Silicate slag from the Victor Chemical Company phosphorus furnace at Tarpon Springs, Fla., has been found to consist essentially of pseudowollastonite, α-CaSiO 3 . The first-formed crystals are euhedral laths which form a mesh making up most of the slag. As the slag continues to solidify, its composition changes slightly and more equant, subhedral crystals of pseudowollastonite are deposited within the framework of the earlier material. Finally, anherdral masses of fibrous, poorly crystallized material are deposited in the remaining pore spaces which are not always completely filled. Spherules of iron phosphide, Fe 2 P, occur very sparsely in the slag as inclusions from the immiscible iron phosphide melt. Uranium content increases in the later crystal products of the slag, and by heavy-liquid fractionation it has been possible to segregate partially the phases and to obtain a fourfold concentration of uranium in 5 percent of the material and a twofold concentration in 30 percent of the material. Nuclear-emulsion studies indicate that the last phases of the silicate slag are actually eight times as radioactive as the early phases. In addition, the iron phosphide spherules are comparably enriches in uranium.

Trace Elements Investigations↗

USGS2018

Biophysical assessment for indemnity selection of Federal Lands in Colorado

Information on the biophysical features of Federal lands identified as suitable for transfer to the State of Colorado was requested by the Bureau of Land Management (BLM). This information is intended for use in conducting an Environmental Assessment prior to the transfer of ownership (conveyance) to the State. The Colorado State Land Board filed a selective application to obtain public land and mineral estate in lieu of lands to which the State of Colorado was entitled but did not receive at the time of statehood. To address this legal obligation, 339 parcels of Federal lands (organized into 89 indemnity units [IUs]), currently under management by the BLM, have been identified as suitable for transfer to the State. The IUs include 23,130 acres of surface and mineral estate and 6,150 acres of mineral estate only. The specific land parcels to be transferred to the State will be finalized after an Environmental Assessment and other evaluations are completed. To provide the biophysical information necessary for conducting a future Environmental Assessment of the potential effects of the proposed land transfer, information on ecological communities, soil characteristics, and land use was summarized at three levels: (1) all of Colorado, (2) lands under the jurisdiction of the BLM, and (3) the 89 IUs. Information was also synthesized and summarized for 179 plant and animal species or subspecies of management concern to evaluate which species had the potential for occurrence on IUs. Datasets summarized for Colorado and for indemnity units and methodological details for all data summaries are provided in U.S. Geological Survey data releases available online at https://doi.org/10.5066/F7GT5MGV and https://doi.org/10.5066/F7C24VQ0 .

Colorado↗

USGS2019

Simulating demography, genetics, and spatially explicit processes to inform reintroduction of a threatened char

The success of species reintroductions can depend on a combination of environmental, demographic, and genetic factors. Although the importance of these factors in the success of reintroductions is well‐accepted, they are typically evaluated independently, which can miss important interactions. For species that persist in metapopulations, movement through and interaction with the landscape is predicted to be a vital component of persistence. Simulation‐based approaches are a promising technique for evaluating the independent and combined effects of these factors on the outcome of various reintroduction and associated management actions. We report results from a simulation study of bull trout ( Salvelinus confluentus ) reintroduction to three watersheds of the Pend Oreille River system in northeastern Washington State, USA. We used an individual‐based, spatially explicit simulation model to evaluate how reintroduction strategies, life history variation, and riverscape structure (e.g., network topology) interact to influence the demographic and genetic characteristics of reintroduced bull trout populations in three watersheds. Simulation scenarios included a range of initial genetic stocks (informed by empirical bull trout genetic data), variation in migratory tendency and life history, and two landscape connectivity alternatives representing a connected network (isolation‐by‐distance) and a fragmented network (isolation‐by‐barrier, using the known existing barriers). A novel feature of these simulations was the ability to consider the interaction of both demographic and genetic (i.e., demogenetic) factors in riverscapes with implicit asymmetric movement probabilities across the barriers. We found that connectivity (presence or absence of barriers) had the largest effect on demographic and genetic outcomes over 200 yr, with a greater effect than both initial genetic diversity and life history variation. We also identified regions of the study system in which bull trout populations persisted across a wide range of demographic, life history, and environmental connectivity parameters. Finally, we found no evidence that initial neutral genetic diversity influenced genetic diversity and structure after 200 yr; instead, genetic drift due to stray rate and population isolation dominated and erased any initial differences in genetic diversity. Our results highlight the utility of spatially explicit demogenetic approaches in exploring and understanding population dynamics—and their implications for management strategies—in fresh waters.

Washington↗

USGS2016

Quaternary geologic map of the Wolf Point 1° × 2° quadrangle, Montana and North Dakota

The Wolf Point quadrangle encompasses approximately 16,084 km 2 (6,210 mi 2 ). The northern boundary is the Montana/Saskatchewan (U.S.-Canada) boundary. The quadrangle is in the Northern Plains physiographic province and it includes the Peerless Plateau and Flaxville Plain. The primary river is the Missouri River. The map units are surficial deposits and materials, not landforms. Deposits that comprise some constructional landforms (for example, ground-moraine deposits, end-moraine deposits, and stagnation-moraine deposits, all composed of till) are distinguished for purposes of reconstruction of glacial history. Surficial deposits and materials are assigned to 23 map units on the basis of genesis, age, lithology or composition, texture or particle size, and other physical, chemical, and engineering characteristics. It is not a map of soils that are recognized in pedology or agronomy. Rather, it is a generalized map of soils recognized in engineering geology, or of substrata or parent materials in which pedologic or agronomic soils are formed. Glaciotectonic (ice-thrust) structures and deposits are mapped separately, represented by a symbol. The surficial deposits are glacial, ice-contact, glaciofluvial, alluvial, lacustrine, eolian, colluvial, and mass-movement deposits. Till of late Wisconsin age is represented by three map units. Till of Illinoian age also is mapped. Till deposited during pre-Illinoian glaciations is not mapped, but is widespread in the subsurface. Linear ice-molded landforms (primarily drumlins), shown by symbol, indicate directions of ice flow during late Wisconsin and Illinoian glaciations. The Quaternary geologic map of the Wolf Point quadrangle, northeastern Montana and North Dakota, was prepared to provide a database for compilation of a Quaternary geologic map of the Regina 4° × 6° quadrangle, United States and Canada, at scale 1:1,000,000, for the U.S. Geological Survey Quaternary Geologic Atlas of the United States map series. This map was compiled from data from many sources, at several different map scales. That information was generalized and simplified, and then transferred to a base map at 1:250,000 scale to serve as the base for final reduction to 1:1,000,000, the nominal reading scale of maps in the Quaternary Geologic Atlas of the United States map series. This map is the generalized and simplified 1:250,000 scale compilation. Letter symbols for the map units are those used for the same units in the Quaternary Geologic Atlas of the United States map series. The map summarizes new, and selected published and unpublished, geologic information for public use and for use by Federal, State, and local governmental agencies for land use planning, including assessment of natural resources, natural hazards, recreation potential, and land use management. It also is a base from which a variety of maps relating to earth surface processes and Quaternary geologic history can be derived.

Montana, North Dakota↗

USGS2009

A water-leach procedure for estimating bioaccessibility of elements in soils from transects across the United States and Canada

An objective of the North American Soil Geochemical Landscapes Project is to provide relevant data concerning bioaccessible concentrations of elements in soil to government and other institutions undertaking environmental studies. A protocol was developed that employs a 1-g soil sample agitated overnight with 40 mL of reverse-osmosis de-ionized water for 20 h, and determination of 63 elements following three steps of centrifugation by inductively coupled plasma–atomic emission spectrometry and inductively coupled plasma–mass spectrometry the following day. Statistical summaries are presented for those 48 elements (Ag, Al, As, B, Ba, Be, Br, Ca, Cd, Ce, Co, Cr, Cs, Cu, Dy, Er, Eu, Fe, Ga, Gd, Ge, Hf, Ho, I, K, La, Li, Lu, Mg, Mn, Mo, Na, Nb, Nd, Ni, P, Pb, Pr, Rb, Re, S, Sb, Si, Sm, Sn, Sr, Tb, Ti, Tl, Tm, U, V, W, Y, Yb, Zn, Zr, and pH) for which <20% of their data were reported as below the detection limit. The resulting data set contains analyses for 161 A-horizon soils collected along two transects, one along the 38th parallel across the USA and the other from northern Manitoba to the USA–Mexico border. The spatial distribution of three selected elements (Ca, Cu, and Pb) along the two transects is discussed in this paper both as absolute amounts liberated by the leach and expressed as a percentage of the total, or near-total, amounts determined for the elements. The Ca data reflect broad trends in soil parent materials, their weathering, and subsequent soil development. Calcium concentrations are generally found to be lower in the older soils of the eastern USA. The Cu data are higher in the eastern half of the USA, correlating with soil organic C, with which it is sequestered. The Pb data exhibit little regional variability due to natural sources, but are influenced by anthropogenic sources. Based on the Pb results, the percentage water-extractable data demonstrate promise as a tool for identifying anthropogenic components. The soil–water partition (distribution) coefficients, K d s (L/kg), were determined and their relevance to estimating bioaccessible amounts of elements to soil fauna and flora is discussed. Finally, a possible link between W concentrations in human urine and water-extractable W levels in Nevada soils is discussed.

Applied Geochemistry↗