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At least 1,099 records · Page 61Linked to original sources
USGS2024

The addition of 144Nd atomic mass to routine ICP-MS analysis as a Quick Screening Tool for Approximating Rare Earth Elements (Q-STAR) in natural waters

Rare earth elements (REEs) are a class of critical minerals, all of which can have supply chain vulnerability that impacts economic security. These elements are widely measured in environmental matrices via inductively coupled plasma mass spectrometry (ICP-MS); however, successful quantification can require time-consuming, sample-specific optimization. While a sample-by-sample approach is appropriate for targeted quantification studies, this approach is not suitable for mineral exploration efforts where rapidly screening thousands of samples for the presence of REEs is desired. Here, we demonstrated the use of a Quick Screening Tool for Approximating REEs (Q-STAR) to detect REEs in surface water and groundwater matrices, collected as part of existing environmental studies. A mass-to-charge ratio of 144 ( m / z = 144) was added to an ICP-MS method to screen for REEs in filtered water samples submitted for metals analyses to the U.S. Geological Survey (USGS) National Water Quality Laboratory. We detected the presence of REEs above a reference threshold of 1200 counts per second in 18 % of pre-selected 6626 samples. Using this screened dataset, we mapped estimated dissolved REE concentrations across the United States in relation to ecoregions and underlying geology. Data are constrained to where sample collection took place but nevertheless show estimated aqueous dissolved REE concentrations on a geographic scale that has not yet been studied. To validate Q-STAR, REEs were measured in a USGS standard reference sample, a subset of 88 archived filtered water samples, and in fresh filtered surface water samples. Our targeted analyses demonstrated a strong linear relationship between Q-STAR predicted and measured values in all archived samples for Nd (r 2 = 0.94), and light REEs (LREEs) such as lanthanum (La) (r 2 = 0.93), praseodymium (Pr) (r 2 = 0.94) and samarium (Sm) (r 2 = 0.94). Using Q-STAR screen values, nine field sites were identified and surface water samples recollected to confirm the continued presence of Nd and LREEs. Q-STAR can be used to screen an unlimited number of water samples for the presence of REEs prior to time-intensive and costly quantitative analyses and to generate large REE datasets for further investigation.

Journal of Geochemical Exploration↗
USGS1999

Use of historical and geospatial data to guide the restoration of a Lake Erie coastal marsh

Historical and geospatial data were used to identify the relationships between water levels, wetland vegetation, littoral drift of sediments, and the condition of a protective barrier beach at Metzger Marsh, a coastal wetland in western Lake Erie, to enhance and guide a joint federal and state wetland restoration project. Eleven sets of large-scale aerial photographs dating from 1940 through 1994 were interpreted to delineate major vegetation types and boundaries of the barrier beach. A geographic information system (GIS) was then used to digitize the data and calculate the vegetated area and length of barrier beach. Supplemented by paleoecological and sedimentological analyses, aerial photographic interpretation revealed that Metzger Marsh was once a drowned-river-mouth wetland dominated by sedges and protected by a sand barrier beach. Extremely high water levels, storm events, and reduction of sediments in the littoral drift contributed to the complete destruction of the barrier beach in 1973 and prevented its recovery. The extent of wetland vegetation, correlated to water levels and condition of the barrier beach, decreased from a high of 108 ha in 1940 to a low of 33 ha in 1994. The lack of an adequate sediment supply and low probability of a period of extremely low lake levels in the near future made natural reestablishment of the barrier beach and wetland vegetation unlikely. Therefore, the federal and state managers chose to construct a dike to replace the protective barrier beach. Recommendations stemming from this historical analysis, however, resulted in the incorporation of a water-control structure in the dike that will retain a hydrologic connection between wetland and lake. Management of the wetland will seek to mimic processes natural to the wetland type identified by this analysis.

Wetlands↗
USGS1995

Synthesis of nutrient and sediment data for watersheds within the Chesapeake Bay drainage basin

Nutrient and sediment data collected by Federal and state agencies from 1972 through 1992 at 1,058 surface-water sites in nontidal parts of the Chesapeake Bay Basin were compiled into a large database. Adequate nutrient, sediment, and streamflow data were not available to compute annual loads for all sites because water-quality monitoring at many of the sites was either short term or noncontinuous or because stream-flow was not measured. Annual nutrient and sediment loads were calculated at a total of 127 sites. Annual loads of dissolved nitrate were calculated for 108 sites, but total nitrogen loads could be calculated for only 48 of these sites because ammonia plus organic nitrogen data were not available for many of these 108 sites. Annual loads of total phosphorus were calculated for 99 sites, and annual loads of suspended sediment were calculated for 33 sites. Loads could be calculated for only a very few sites in the Juniata River Basin (a tributary to the Susquehanna River), the York River Basin, the middle and lower reaches of the James River, and the nontidal parts of the eastern shore of the Bay. Geographic Information System (GIS) spatial data sets of land use, physiographic province, rock type, and watershed delineation were compiled for the entire Chesapeake Bay Basin (approximately 64,000 square miles). The nutrient- and sediment-yield were evaluated with respect to land use, physiographic province, rock type, and hydrologic characteristics. During years that the mean streamflow was about equal to the long-term mean streamflow, the Susquehanna River contributed about 50 percent of the freshwater, 66 percent of the total nitrogen, and 40 percent of the total phosphorus transported by tributaries to the Bay. Nutrient and sediment data were available for less than 18 percent of the predominantly agricultural areas underlain by siliciclastic rock and for less than 35 percent of the predominantly agricultural areas underlain by either carbonate rock or unconsolidated rock. Nutrient and sediment data were available for about 91 percent of the predominantly forested areas underlain by siliciclastic rock. Spatial and temporal gaps in the water-quality data and GIs data sets limited some data analysis. Correlations of annual yields or nutrients and sediment with respect to land use, physiographic province, and rock type indicated (1) basins with larger percentages of agricultural land had larger nutrient and sediment yields, (2) basins with larger percentages of forest land had smaller nutrient and sediment loads, (3) the largest total nitrogen yields were from agricultural basins underlain by carbonate rock, (4) yields or nutrients from urban basins were substantially less than yields from agricultural basins, and (5) basins with small amounts of agricultural and urban land had relatively small nutrient and sediment yields.

Chesapeake Bay drainage basin↗
USGS2009

Geospatial data to support analysis of water-quality conditions in basin-fill aquifers in the southwestern United States

The Southwest Principal Aquifers study area consists of most of California and Nevada and parts of Utah, Arizona, New Mexico, and Colorado; it is about 409,000 square miles. The Basin-fill aquifers extend through about 201,000 square miles of the study area and are the primary source of water for cities and agricultural communities in basins in the arid and semiarid southwestern United States (Southwest). The demand on limited ground-water resources in areas in the southwestern United States has increased significantly. This increased demand underscores the importance of understanding factors that affect the water quality in basin-fill aquifers in the region, which are being studied through the U.S. Geological Survey's National Water-Quality Assessment (NAWQA) program. As a part of this study, spatial datasets of natural and anthropogenic factors that may affect ground-water quality of the basin-fill aquifers in the southwestern United States were developed. These data include physical characteristics of the region, such as geology, elevation, and precipitation, as well as anthropogenic factors, including population, land use, and water use. Spatial statistics for the alluvial basins in the Southwest have been calculated using the datasets. This information provides a foundation for the development of conceptual and statistical models that relate natural and anthropogenic factors to ground-water quality across the Southwest. A geographic information system (GIS) was used to determine and illustrate the spatial distribution of these basin-fill variables across the region. One hundred-meter resolution raster data layers that represent the spatial characteristics of the basins' boundaries, drainage areas, population densities, land use, and water use were developed for the entire Southwest.

Arizona, California, Colorado, Nevada, New Mexico,↗
USGS2023

User’s Guide to planetary image analysis and geologic mapping in ArcGIS Pro

Geologic maps are valuable tools in planetary science. Though planetary geologic maps are similar to terrestrial (Earthbased) geologic maps, the nature of planetary exploration introduces unique challenges for geologic mappers. Terrestrial geologic mappers prepare products from field-based observation, often comparing or refining those with aerial and (or) orbital images. Planetary geologic mapping relies almost exclusively on remote observations, which are made by orbiting spacecraft. Therefore, with a few exceptions for locations with rovers, landers, or crewed surface missions, planetary geologic mappers are not able to observe their map area in detail or at smaller scales. As a result, they must interpret and describe their map features differently than those used in terrestrial geologic maps. For example, terrestrial geologic mappers commonly divide units by lithology (rock type) or grain size. However, planetary geologic mappers often do not have detailed enough information to know what type of rock or grain size is present, and instead must divide the planet’s surface into geologic units using differences in tone, color, and surface texture (at multiple scales). Cross-cutting relationships, where apparent, can provide excellent—and often crucial—observations for identifying and subdividing geologic units using orbital datasets. The process of creating planetary maps has evolved over time, from original hand-drawn maps created during the early 1800s through the late 1900s, to the fully digital products created today. Modern-day planetary geologic mapping uses Geographic Information Systems (GIS) software and tools to visualize data, delineate units and landforms, and accurately convey spatial relationships to a map user using cartographic features represented by points, lines, and polygons. This tutorial was written to familiarize both new and experienced planetary geologic mappers with ArcGIS Pro, a commonly used GIS software package developed by Esri. This tutorial introduces new planetary geologic mappers to fundamental concepts and best practices in planetary geologic mapping. For mappers with experience using ArcMap (a previous version of ArcGIS), this tutorial will help to familiarize users with new changes in layout and functionality, so current projects may be migrated into the ArcGIS Pro environment. No prior knowledge is required, although a general familiarity with geology, GIS, and planetary science is recommended. This tutorial includes links to helpful glossaries of common GIS terms and other GIS and planetary science resources in appendix 1. For additional information on planetary geologic mapping, see the U.S Geological Survey (USGS) Astrogeology NASA Planetary Geologic Mapping Program website and the Planetary Mapping Guidelines. Numerous ArcGIS tutorials are also available from Esri’s Tutorials page, through the Esri Academy catalog, and Esri’s ArcGIS Pro Resources page.

Techniques and Methods↗
USGS2006

Variation in spring nearshore resident fish species composition and life histories in the lower San Joaquin watershed and delta

Providing freshwater to human populations while protecting or rehabilitating ecosystem health is a significant challenge to water resource managers and requires accurate knowledge of aquatic resources. Previous studies of fish assemblages in the San Francisco Estuary and watershed have focused on specific habitat types, water bodies, or geographic subregions. In this study, we use seining data from two monitoring programs to provide an integrated view of spring nearshore resident fish species composition and life history characteristics in five regions: the San Joaquin River, the upper Sacramento River, the lower Sacramento River, the northern Sacramento-San Joaquin Delta (North Delta), and the Interior Delta. Data for the period March-May from 1994 to 2002, showed that spring species composition of the San Joaquin River was very different from the other four regions. Total catch in the San Joaquin River was dominated by small, short-lived batch spawning alien species (93%), particularly red shiner Cyprinella lutrensis (>75% of total catch). The upper and lower Sacramento River were very similar in species composition and life history characteristics and less dominated by alien fish (<45% of total catch). Ordination of species percentage abundances by non–metric multidimensional scaling confirmed that the major gradient was from assemblages dominated by native species to assemblages dominated by alien species. Two-way analysis of variance of ordination scores indicated that spatial variability was more important than annual variability in explaining patterns in species composition. The potential benefits of San Joaquin River native fish restoration appear high because there is so much potential for improvement; however, it is unclear how to best manipulate the system to achieve such restoration. Addressing such uncertainties is necessary if society desires the reservation and restoration of native biodiversity as human demands on water resources increase.

California↗
USGS2013

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Katawas mineral district in Afghanistan: Chapter N 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 Katawas mineral district, which has 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 (©AXA, 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 Katawas) and the WGS84 datum. The final image mosaics 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 Katawas study area, one subarea was designated for detailed field investigation (that is, the Gold subarea); this subarea was extracted from the area's image mosaic and is provided as a separate embedded geotiff image.

Katawas Mineral District↗
USGS2013

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Nuristan 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 Nuristan mineral district, which has gem, lithium, and cesium 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. All available panchromatic images for this area had significant cloud and snow cover that precluded their use for resolution enhancement of the multispectral image data. Each of the four-band images within the 10-m 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 Nuristan) and the WGS84 datum. The final image mosaics for the Nuristan 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.

Data Series↗
USGS2011

Forecasting carbon budget under climate change and CO2 fertilization for subtropical region in China using integrated biosphere simulator (IBIS) model

The regional carbon budget of the climatic transition zone may be very sensitive to climate change and increasing atmospheric CO2 concentrations. This study simulated the carbon cycles under these changes using process-based ecosystem models. The Integrated Biosphere Simulator (IBIS), a Dynamic Global Vegetation Model (DGVM), was used to evaluate the impacts of climate change and CO2 fertilization on net primary production (NPP), net ecosystem production (NEP), and the vegetation structure of terrestrial ecosystems in Zhejiang province (area 101,800 km2, mainly covered by subtropical evergreen forest and warm-temperate evergreen broadleaf forest) which is located in the subtropical climate area of China. Two general circulation models (HADCM3 and CGCM3) representing four IPCC climate change scenarios (HC3AA, HC3GG, CGCM-sresa2, and CGCM-sresb1) were used as climate inputs for IBIS. Results show that simulated historical biomass and NPP are consistent with field and other modelled data, which makes the analysis of future carbon budget reliable. The results indicate that NPP over the entire Zhejiang province was about 55 Mt C yr-1 during the last half of the 21st century. An NPP increase of about 24 Mt C by the end of the 21st century was estimated with the combined effects of increasing CO2 and climate change. A slight NPP increase of about 5 Mt C was estimated under the climate change alone scenario. Forests in Zhejiang are currently acting as a carbon sink with an average NEP of about 2.5 Mt C yr-1. NEP will increase to about 5 Mt C yr-1 by the end of the 21st century with the increasing atmospheric CO2 concentration and climate change. However, climate change alone will reduce the forest carbon sequestration of Zhejiang's forests. Future climate warming will substantially change the vegetation cover types; warm-temperate evergreen broadleaf forest will be gradually substituted by subtropical evergreen forest. An increasing CO2 concentration will have little contribution to vegetation changes. Simulated NPP shows geographic patterns consistent with temperature to a certain extent, and precipitation is not the limiting factor for forest NPP in the subtropical climate conditions. There is no close relationship between the spatial pattern of NEP and climate condition.

Polish Journal of Ecology↗
USGS2024

Applying mark-resight, count, and telemetry data to estimate effective sampling area and fish density with stationary underwater cameras

Accurate estimates of abundance and density for geographically open populations must account for the effective sampling area (ESA) of sampling gears. We describe a Marked N-Mixture model to estimate ESA and density (number of individuals/unit area) from repeated counts of unmarked and marked individuals, integrating mark-resight, camera counts, and telemetry data of red snapper ( Lutjanus campechanus ) at a 1.6 km 2 reef off North Carolina, USA. Cameras recorded observations of unmarked and marked individuals, whereas telemetry data indicated the number of tagged fish present on the reef. We estimated density (95 individuals/km 2 , 95%CI: 58–149), ESA (which was lower when current direction was towards the camera), detection probability (0.06, 95%CI: 0.03–0.09), and covariate relationships. Simulation studies under different scenarios of data quality and space use identified positive bias in density estimates from N-mixture models due to fish movement. In contrast, the Marked N-Mixture model returned unbiased estimates of density, ESA, and detection parameters, and appears to be a more robust method for modeling density given the data available for this analysis. This approach can be applied to other populations where count and telemetry data overlap in space and time.

North Carolina↗
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↗
USGS2015

Evaluation of groundwater levels in the South Platte River alluvial aquifer, Colorado, 1953-2012, and design of initial well networks for monitoring groundwater levels

The South Platte River and underlying alluvial aquifer form an important hydrologic resource in northeastern Colorado that provides water to population centers along the Front Range and to agricultural communities across the rural plains. Water is regulated based on seniority of water rights and delivered using a network of administration structures that includes ditches, reservoirs, wells, impacted river sections, and engineered recharge areas. A recent addendum to Colorado water law enacted during 2002-2003 curtailed pumping from thousands of wells that lacked authorized augmentation plans. The restrictions in pumping were hypothesized to increase water storage in the aquifer, causing groundwater to rise near the land surface at some locations. The U.S. Geological Survey (USGS), in cooperation with the Colorado Water Conservation Board and the Colorado Water Institute, completed an assessment of 60 years (yr) of historical groundwater-level records collected from 1953 to 2012 from 1,669 wells. Relations of "high" groundwater levels, defined as depth to water from 0 to 10 feet (ft) below land surface, were compared to precipitation, river discharge, and 36 geographic and administrative attributes to identify natural and human controls in areas with shallow groundwater. Averaged per decade and over the entire aquifer, depths to groundwater varied between 24 and 32 ft over the 60-yr record. The shallowest average depth to water was identified during 1983-1992, which also recorded the highest levels of decadal precipitation. Average depth to water was greatest (32 ft) during 1953-1962 and intermediate (30 ft) in the recent decade (2003-2012) following curtailment of pumping. Between the decades 1993-2002 and 2003-2012, groundwater levels declined about 2 ft across the aquifer. In comparison, in areas where groundwater levels were within 20 ft of the land surface, observed groundwater levels rose about 0.6 ft, on average, during the same period, which demonstrated preferential rise in areas with shallow groundwater. Approximately 29 percent of water-level observations were identified as high groundwater in the South Platte River alluvial aquifer over the 60-yr record. High groundwater levels were found in 17 to 33 percent of wells examined by decade, with the largest percentages occurring over three decades from 1963 to 1992. The recent decade (2003-2012) exhibited an intermediate percentage (25 percent) of wells with high groundwater levels but also had the highest percentage (30 percent) of high groundwater observations, although results by observations were similar (26-29 percent) over three decades prior, from 1963 to 1992. Major sections of the aquifer from north of Sterling to Julesburg and areas near Greeley, La Salle, and Gilcrest were identified with the highest frequencies of high groundwater levels. Changes in groundwater levels were evaluated using Kendal line and least trimmed squares regression methods using a significance level of 0.01 and statistical power of 0.8. During 2003-2012, following curtailment of pumping, 88 percent of wells and 81 percent of subwatershed areas with significant trends in groundwater levels exhibited rising water levels. Over the complete 60-yr record, however, 66 percent of wells and 57 percent of subwatersheds with significant groundwater-level trends still showed declining water levels; rates of groundwater-level change were typically less than 0.125 ft/yr in areas near the South Platte River, with greater declines along the southern tributaries. In agreement, 58 percent of subwatersheds evaluated between 1963-1972 and 2003-2012 showed net declines in average decadal groundwater levels. More areas had groundwater decline in upgradient sections to the west and rise in downgradient sections to the east, implying a redistribution of water has occurred in some areas of the aquifer. Precipitation was identified as having the strongest statistically significant correlations to river discharge over annual and decadal periods (Pearson correlation coefficients of 0.5 and 0.8, respectively, and statistical significance defined by p-values less than 0.05). Correlation coefficients between river discharge and frequency of high groundwater levels were statistically significant at 0.4 annually and 0.6 over decadal periods, indicating that periods of high river flow were often coincident with high groundwater conditions. Over seasonal periods in five of the six decades examined, peak high groundwater levels occurred after spring runoff from July to September when administrative structures were most active. Between 1993-2002 and 2003-2012, groundwater levels rose while river discharge decreased, in part from greater reliance on surface water and curtailed pumping from wells without augmentation plans. Geographic attributes of elevation and proximity to streams and rivers showed moderate correlations to high groundwater levels in wells used for observing groundwater levels (correlation coefficients of 0.3 to 0.4). Local depressions and regional lows within the aquifer were identified as areas of potential shallow groundwater. Wells close to the river regularly indicated high groundwater levels, while those within depleted tributaries tended to have low frequencies of high groundwater levels. Some attributes of administrative structures were spatially correlated to high groundwater levels at moderate to high magnitudes (correlation coefficients of 0.3 to 0.7). The number of affected river reaches or recharge areas that surround a well where groundwater levels were observed and its distance from the nearest well field showed the strongest controls on high groundwater levels. Influences of administrative structures on groundwater levels were in some cases local over a mile or less but could extend to several miles, often manifesting as diffuse effects from multiple surrounding structures. A network of candidate monitoring wells was proposed to initiate a regional monitoring program. Consistent monitoring and analysis of groundwater levels will be needed for informed decisions to optimize beneficial use of water and to limit high groundwater levels in susceptible areas. Finalization of the network will require future field reconnaissance to assess local site conditions and discussions with State authorities.

Colorado↗
USGS2013

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Takhar mineral district in Afghanistan: Chapter Q 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 Takhar mineral district, which has industrial evaporite 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. 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 Takhar) and the WGS84 datum. The final image mosaics for the Takhar 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.

Takhar Mineral District↗
USGS2013

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the South Bamyan 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 South Bamyan mineral district, which has areas with a spectral reflectance anomaly that require field investigation. 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 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 South Bamyan) and the WGS84 datum. The final image mosaics for the South Bamyan 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.

South Bamyan Mineral District↗
USGS2006

Preliminary integrated geologic map databases for the United States: Connecticut, Maine, Massachusetts, New Hampshire, New Jersey, Rhode Island and Vermont

The rapid growth in the use of Geographic Information Systems (GIS) has highlighted the need for regional and national scale digital geologic maps that have standardized information about geologic age and lithology. Such maps can be conveniently used to generate derivative maps for manifold special purposes such as mineral-resource assessment, metallogenic studies, tectonic studies, and environmental research. Although two digital geologic maps (Schruben and others, 1994; Reed and Bush, 2004) of the United States currently exist, their scales (1:2,500,000 and 1:5,000,000) are too general for many regional applications. Most states have digital geologic maps at scales of about 1:500,000, but the databases are not comparably structured and, thus, it is difficult to use the digital database for more than one state at a time. This report describes the result for a seven state region of an effort by the U.S. Geological Survey to produce a series of integrated and standardized state geologic map databases that cover the entire United States. In 1997, the United States Geological Survey's Mineral Resources Program initiated the National Surveys and Analysis (NSA) Project to develop national digital databases. One primary activity of this project was to compile a national digital geologic map database, utilizing state geologic maps, to support studies in the range of 1:250,000- to 1:1,000,000-scale. To accomplish this, state databases were prepared using a common standard for the database structure, fields, attribution, and data dictionaries. For Alaska and Hawaii new state maps are being prepared and the preliminary work for Alaska is being released as a series of 1:250,000 scale quadrangle reports. This document provides background information and documentation for the integrated geologic map databases of this report. This report is one of a series of such reports releasing preliminary standardized geologic map databases for the United States. The data products of the project consist of two main parts, the spatial databases and a set of supplemental tables relating to geologic map units. The datasets serve as a data resource to generate a variety of stratigraphic, age, and lithologic maps. This documentation is divided into four main sections: (1) description of the set of data files provided in this report, (2) specifications of the spatial databases, (3) specifications of the supplemental tables, and (4) an appendix containing the data dictionaries used to populate some fields of the spatial database and supplemental tables.

Connecticut, Maine, Massachusetts, New Hampshire, ↗
USGS1991

National water summary 1988–89 — Hydrologic events and floods and droughts

National Water Summary 1988-89 - Hydrologic Events and Floods and Droughts documents the occurrence in the United States, Puerto Rico, and the U.S. Virgin Islands of two types of extreme hydrologic events floods and droughts on the basis of analysis of stream-discharge data. This report details, for the first time, the areal extent of the most notable floods and droughts in each State, portrays their severity in terms of annual peak discharge for floods and annual departure from long-term discharge for droughts for selected stream-gaging stations, and estimates how frequently floods and droughts of such severity can be expected to recur. These two types of extreme hydrologic events are very different in their duration, cause, areal extent, and effect on human activities. Floods are short-term phenomena that typically last only a few hours to a few days and are associated with weather systems that produce unusually large amounts of rain or that cause snow to melt quickly. The large amount of runoff produced causes rivers to overflow their banks and, thus, is highly dangerous to human life and property. In contrast, droughts are long-term phenomena that typically persist for months to a decade or more and are associated with the absence of precipitation producing weather. They affect large geographic areas that can be statewide, regional, or even nationwide in extent. Droughts can cause great economic hardship and even loss of life in developing countries, although the loss of life results almost wholly from diminished water supplies and catastrophic crop failures rather than from the direct and obvious peril to human life that is common to floods. The following discussion is an overview of the three parts of this 1988-89 National Water Summary "Hydrologic Conditions and Water-Related Events, Water Years 1988-89," "Hydrologic Perspectives on Water Issues," and "State Summaries of Floods and Droughts." Background information on sources of atmospheric moisture to the States from a study sponsored by the U.S. Geological Survey to enable related information to be presented in each of the State summaries also is given.

Water Supply Paper↗
USGS2011

A geographic information system tool for aquatic resource conservation in the Red and Sabine River Watersheds of the southeast United States

Our goal was to build a geographic information system (GIS) tool to enhance modeling and hypothesis testing relevant to watersheds and fish fauna of the Red and Sabine Rivers in the southeastern United States. Species of concern were identified from wildlife action plans and Web sites. Spatial distributions of fish species and mercury in fillets were delineated using data from states. Public georeferenced data were obtained on land cover, soil type, forest canopy, impervious surfaces, wastewater facilities and 303(d) impaired waters. Overlay maps highlighted patterns across 8-digit hydrologic unit codes (HUCs). Bossier City, Louisiana and Beaumont, Texas areas displayed impervious surfaces over 10% and 303(d) waters per HUC were 20% and 8%, respectively. Because bowfin (Amia calva) (n=299) and bass (Micropterus spp.) (n=1493) occurred in up to 44% of HUCs and fillets contained elemental mercury concentrations across ranges monitored, they were appropriate indicators of bioavailable mercury. Of the total fish number showing >0.5ppm, 81% of records were derived from bowfin and bass, and stepwise multiple linear regressions indicated fish with mercury at these concentrations correlated with environmental variables. Detrended correspondence analysis showed total species occurrence and environmental relationships significant, where 81.6% of the variability in fish occurrence was explained by impervious surface, land cover other than canopy or impervious surface (such as wetlands and agricultural area) and canopy (forest type). Two-way indicator species analysis delineated species co-occurrence in HUCs (14 groups) and similarity of species composition (nine groups). Results identified three HUC groupings as potential targets for managerial interest. Quality control concerns for GIS development included site name data and priority rankings of critical fish species. This tool can be used to support modeling and trend analyses for several purposes, such as those relevant for developing and reporting on water quality standards and critical habitat assessments.

Arkansas, Louisiana, Oklahoma, Texas↗