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USGS2013

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Herat mineral district in Afghanistan: Chapter T 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 Herat mineral district, which has barium and limestone 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,2007,2008,2009), 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 1,000-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 (41 for Herat) 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 Herat 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 Herat study area, one subarea was designated for detailed field investigations (that is, the Barium-Limestone subarea); this subarea was extracted from the area's image mosaic and is provided as separate embedded geotiff images.

Herat↗
USGS2026

Re-examining the growing degree day minimum for grass carp spawning initiation in Lake Erie: Have we missed the mark?

Understanding the timing of life history processes of invasive fish species, such as adult aggregations during spawning, allows natural resource managers to optimize targeted population control efforts. Temperature-based estimates of the timing of spawning initiation for grass carp ( Ctenopharyngodon idella ) exist from its native range, but have not previously been developed for grass carp reproduction in its invaded range in the Laurentian Great Lakes of North America. We accounted for differences among methods across studies and calculated cumulative growing degree days (GDD) for the dates of grass carp egg capture in Lake Erie tributaries (Sandusky, Maumee, and Huron rivers) during 2015–2024 and compared these values to the existing GDD base 15°C requirement estimate from the native range (633 GDD–15°C). The earliest egg detection in Lake Erie (Sandusky River) was 19 GDD–15°C or 361 GDD–5°C (latest egg detection was 2285 GDD–5°C from the Sandusky River), indicating that spawning was initiated up to 25 days earlier than would be predicted by the native range GDD. Moreover, spawning in Lake Erie tributaries occurred earlier than predicted for 58% of spawning events examined based on the native range GDD. The GDD values for spawning initiation in Lake Erie tributaries can be used to refine the timing of control efforts targeting pre-spawn and spawning adult fish, inform the timing of egg sampling, and provide linkages to existing early life stage models to infer the length of the growing season available for age-0 fish to reassess tributary suitability.

Ohio↗
USGS2012

Development of a flood-warning system and flood-inundation mapping in Licking County, Ohio

Digital flood-inundation maps for selected reaches of South Fork Licking River, Raccoon Creek, North Fork Licking River, and the Licking River in Licking County, Ohio, were created by the U.S. Geological Survey (USGS), in cooperation with the Ohio Department of Transportation; U.S. Department of Transportation, Federal Highway Administration; Muskingum Watershed Conservancy District; U.S. Department of Agriculture, Natural Resources Conservation Service; and the City of Newark and Village of Granville, Ohio. The inundation maps depict estimates of the areal extent of flooding corresponding to water levels (stages) at the following USGS streamgages: South Fork Licking River at Heath, Ohio (03145173); Raccoon Creek below Wilson Street at Newark, Ohio (03145534); North Fork Licking River at East Main Street at Newark, Ohio (03146402); and Licking River near Newark, Ohio (03146500). The maps were provided to the National Weather Service (NWS) for incorporation into a Web-based flood-warning system that can be used in conjunction with NWS flood-forecast data to show areas of predicted flood inundation associated with forecasted flood-peak stages. As part of the flood-warning streamflow network, the USGS re-installed one streamgage on North Fork Licking River, and added three new streamgages, one each on North Fork Licking River, South Fork Licking River, and Raccoon Creek. Additionally, the USGS upgraded a lake-level gage on Buckeye Lake. Data from the streamgages and lake-level gage can be used by emergency-management personnel, in conjunction with the flood-inundation maps, to help determine a course of action when flooding is imminent. Flood profiles for selected reaches were prepared by calibrating steady-state step-backwater models to selected, established streamgage rating curves. The step-backwater models then were used to determine water-surface-elevation profiles for up to 10 flood stages at a streamgage with corresponding streamflows ranging from approximately the 50 to 0.2-percent chance annual-exceedance probabilities for each of the 4 streamgages that correspond to the flood-inundation maps. The computed flood profiles were used in combination with digital elevation data to delineate flood-inundation areas. Maps of Licking County showing flood-inundation areas overlain on digital orthophotographs are presented for the selected floods. The USGS also developed an unsteady-flow model for a reach of South Fork Licking River for use by the NWS to enhance their ability to provide advanced flood warning in the region north of Buckeye Lake, Ohio. The unsteady-flow model was calibrated based on data from four flooding events that occurred from June 2008 to December 2011. Model calibration was approximate due to the fact that there were unmeasured inflows to the river that were not able to be considered during the calibration. Information on unmeasured inflow derived from NWS hydrologic models and additional flood-event data could enable the NWS to further refine the unsteady-flow model.

Ohio↗
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↗
USGS2012

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Khanneshin mineral district in Afghanistan: Chapter A 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 Khanneshin mineral district, which has uranium, thorium, rare-earth-element, and apatite 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,2007,2008,2010), 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 (41 for Khanneshin) and the WGS84 datum. The final image mosaics were subdivided into nine overlapping tiles or quadrants because of the large size of the target area. The nine image tiles (or quadrants) for the Khanneshin 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 Khanneshin study area, one subarea was designated for detailed field investigations (that is, the Khanneshin volcano subarea); this subarea was extracted from the area's image mosaic and is provided as separate embedded geotiff images.

Helm;Nimroz↗
USGS2012

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Haji-Gak mineral district in Afghanistan: Chapter C 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 Haji-Gak mineral district, which has iron ore 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,2006,2007), 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 co-registered 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 Haji-Gak) and the WGS84 datum. The final image mosaics were subdivided into three overlapping tiles or quadrants because of the large size of the target area. The three image tiles (or quadrants) for the Haji-Gak 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 Haji-Gak study area, three subareas were designated for detailed field investigations (that is, the Haji-Gak Prospect, Farenjal, and NE Haji-Gak subareas); these subareas were extracted from the area's image mosaic and are provided as separate embedded geotiff images.

Bamyan;Parwan;Wardak↗
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 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

Chapter 5. Assessment of undiscovered conventional oil and gas resources-Lower Cretaceous Travis Peak and Hosston formations, Jurassic Smackover interior salt basins total petroleum system, in the East Texas basin and Louisiana-Mississippi salt basins provinces

The Lower Cretaceous Travis Peak Formation of east Texas and southern Arkansas (and the correlative Hosston Formation of Louisiana and Mississippi) is a basinward-thickening wedge of terrigenous clastic sedimentary rocks that underlies the northern Gulf of Mexico Basin from east Texas across northern Louisiana to southern Mississippi. Clastic detritus was derived from two main fluvial-deltaic depocenters, one in northeastern Texas and the other extending from southeastern Mississippi northwestward into northeastern Louisiana. Across the main hydrocarbon-productive trend in east Texas and northern Louisiana, the Travis Peak and Hosston Formations are about 2,000 ft thick. The most likely sources for hydrocarbons in Travis Peak and Hosston reservoirs are two stratigraphically lower units, lime mudstones of the Upper Jurassic Smackover Formation and organic-rich shales of the Upper Jurassic Bossier Shale of the Cotton Valley Group. As a result of the absence of proximal source rocks and a lack of effective migration pathways from stratigraphically or geographically distant source rocks, hydrocarbon charge is sufficient for development of conventional gas accumulations but insufficient for development of basin-centered gas. The petroleum assessment of the Travis Peak and Hosston Formations was conducted by using a total petroleum system model. A total petroleum system includes all of the important elements of a hydrocarbon fluid system needed to develop oil and gas accumulations, including source and reservoir rocks, hydrocarbon generation, migration, traps and seals, and undiscovered accumulations. A total petroleum system is mappable and may include one or more assessment units. For each assessment unit, reservoir rocks contain similar geology, exploration characteristics, and risk. The Jurassic Smackover Interior Salt Basins Total Petroleum System is defined for this assessment to include (1) Upper Jurassic Smackover carbonates and calcareous shales and organic-rich shales of the Upper Jurassic Bossier Shale of the Cotton Valley Group and (2) Lower Cretaceous Travis Peak and Hosston Formations. The Jurassic Smackover Interior Salt Basins Total Petroleum System includes three conventional Travis Peak-Hosston assessment units: Travis Peak-Hosston Gas and Oil (AU 50490205), Travis Peak-Hosston Updip Oil (AU 50490206), and Travis Peak-Hosston Hypothetical Updip Oil (AU 50490207). A fourth assessment unit, the Hosston Hypothetical Slope-Basin Gas Assessment Unit, was named and numbered (AU 50490208) but not geologically defined or quantitatively assessed owing to a lack of data. Together, assessment units 50490205 to 50490207 are estimated to contain a mean undiscovered conventional resource of 29 million barrels of oil, 1,136 billion cubic feet of gas, and 22 million barrels of natural gas liquids.

Alabama, Arkansas. Florida, Georgia, Louisiana, Mi↗
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 Farah 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 Farah mineral district, which has spectral reflectance anomalies indicative of copper, zinc, lead, silver, 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 ((c)JAXA, 2007, 2008, 2010), 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 (41 for Farah) and the WGS84 datum. The final image mosaics were subdivided into four overlapping tiles or quadrants because of the large size of the target area. The four image tiles (or quadrants) for the Farah 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 Farah study area, five subareas were designated for detailed field investigations (that is, the FarahA through FarahE subareas); these subareas were extracted from the area’s image mosaic and are provided as separate embedded geotiff images.

Farah Mineral District↗
USGS2008

Long-term water quality and biological responses to multiple best management practices in Rock Creek, Idaho

Water quality and macroinvertebrate assemblage data from 1981 to 2005 were assessed to evaluate the water quality and biological responses of a western trout stream to the implementation of multiple best management practices (BMPs) on irrigated cropland. Data from Rock Creek near Twin Falls, Idaho, a long-term monitoring site, were assembled from state and federal sources to provide the evaluation. Seasonal loads of the nonpoint source pollutants suspended sediment (SS), total phosphorus (TP), and nitrate-nitrite (NN) were estimated using a regression model with time-series streamflow data and constituent concentrations. Trends in the macroinvertebrate assemblages were evaluated using a number of biological metrics and nonmetric multidimensional scaling ordination. Regression analysis found significant annual decreases in TP and SS flow-adjusted concentrations during the BMP implementation period from 1983 to 1990 of about 7 and 10%, respectively. These results are coincident with the implementation of multiple BMPs on about 75% of the irrigated cropland in the watershed. Macroinvertebrate assemblages during this time also responded with a change in taxa composition resulting in improved biotic index scores. Taxon specific TP and SS optima, empirically derived from a large national dataset, predicted a decrease in SS concentrations of about 37% (52 to 33 mg/l) and a decrease in TP concentrations of about 50% (0.20 to 0.10 mg/l) from 1981 to 1987. Decreasing trends in TP, SS, and NN pollutant loads were primarily the result of naturally low streamflow conditions during the BMP post-implementation period from 1993 to 2005. Trends in macroinvertebrate responses during 1993 to 2005 were confounded by the introduction of the New Zealand mudsnail (Potamopyrgus antipodarum), which approached densities of 100,000 per m 2 in riffle habitat. The occurrence of this invasive species appears to have caused a major shift in composition and function of the macroinvertebrate assemblages. ?? 2008 American Water Resources Association.

Journal of the American Water Resources Associatio↗
USGS2003

The behavior of U- and Th-series nuclides in groundwater

Groundwater has long been an active area of research driven by its importance both as a societal resource and as a component in the global hydrological cycle. Key issues in groundwater research include inferring rates of transport of chemical constituents, determining the ages of groundwater, and tracing water masses using chemical fingerprints. While information on the trace elements pertinent to these topics can be obtained from aquifer tests using experimentally introduced tracers, and from laboratory experiments on aquifer materials, these studies are necessarily limited in time and space. Regional studies of aquifers can focus on greater scales and time periods, but must contend with greater complexities and variations. In this regard, the isotopic systematics of the naturally occurring radionuclides in the U- and Th- decay series have been invaluable in investigating aquifer behavior of U, Th, and Ra. These nuclides are present in all groundwaters and are each represented by several isotopes with very different half-lives, so that processes occurring over a range of time-scales can be studied (Table 1 ⇓ ). Within the host aquifer minerals, the radionuclides in each decay series are generally expected to be in secular equilibrium and so have equal activities (see Bourdon et al. 2003 ). In contrast, these nuclides exhibit strong relative fractionations within the surrounding groundwaters that reflect contrasting behavior during release into the water and during interaction with the surrounding host aquifer rocks. Radionuclide data can be used, within the framework of models of the processes involved, to obtain quantitative assessments of radionuclide release from aquifer rocks and groundwater migration rates. The isotopic variations that are generated also have the potential for providing fingerprints for groundwaters from specific aquifer environments, and have even been explored as a means for calculating groundwater ages.

Reviews in Mineralogy and Geochemistry↗
USGS2007

Investigation of wind and water level for the Giacomini Wetland Restoration Project, Point Reyes National Seashore

Point Reyes National Seashore (PRNS), comprising unique elements of geological, biological, and historical interest, is located on the central California coast approximately 60 km northwest of San Francisco. The National Seashore contains nearly 130 km of exposed and protected shorelines, spectacular coastal cliffs and headlands, lagoons, open grasslands, bushy hillsides, and forested ridges. Approximately 30 km of the shoreline are coastal-dune habitat that supports 11 federally listed species, including the threatened western snowy plover and the endangered plants Tidestrom's lupine ( Lupinus tidestromii ) and beach layia ( Layia carnosa ). The San Andreas Fault, a right-lateral strike-slip fault, trends northwest along the northeastern side of the park. Tomales Bay, which is straight, long, narrow, and shallow, runs along the northeastern boundary of PRNS. The Bay, which fills the northwestern end of a rift valley at the intersection of the San Andreas Fault with the coastline, is approximately 20 km long, 2 km wide, and 6 m deep with mountainous terrain to the southwest and rolling hills to the northeast. Tomales Bay is one of the cleanest estuaries on the West Coast. In winter, approximately 17,000 to 20,000 shorebirds inhabit Tomales Bay and Bodega Bay, which lies directly to the north. At the head of Tomales Bay, the Giacomini Ranch comprises 563 acres of pastureland currently being used for grazing dairy cattle. After more than 50 years of operation as a dairy, the National Park Service acquired the Giacomini property with the intention to restore most of it and the nearby Olema Marsh to tidal wetland. Restoration will add approximately 4% to the existing coastal wetlands in California. The project will return the headwaters of Tomales Bay and two major stream intersections to an intertidal marsh environment, enhancing habitat for both wildlife and fish populations and contributing to the long-term health of Tomales Bay. Prior to the establishment of the ranch, the area was primarily salt marsh that formed as the delta of Lagunitas Creek expanded into Tomales Bay. In converting the salt marsh to dairy land, levees and tide gates were constructed to prevent tidal incursion and stream flooding. Those levees have significantly altered the patterns of estuarine circulation and sediment deposition. To restore natural hydrologic processes within the area and to promote the return of ecological functions and processes, the levees will have to be breached or removed. Developing a successful restoration strategy requires knowledge of elevations within the pastureland and the range of water depths that can be expected from tidal, river, and wind action. In support of the restoration program, the USGS provides technical assistance to PRNS in the form of a scientific study focusing on understanding the physical processes that could affect the Giacomini wetland restoration. The study will yield scientific products that NPS resource managers can use in designing and implementing the restoration project. Research elements include: - Develop a Geodetic Control Network (GCN) throughout PRNS that meets the standards specified National Geodetic Survey data base (the NGS "Bluebook"). The grid will allow this and future studies to be conducted to a precision commensurate with the expressed goals of PRNS. The survey will consist of three steps: (1) verify existing GPS control monuments in the area; (2) tie control monuments in the study areas to the GPS control monuments; and (3) establish NAVD88 elevations using a digital electronic level. - Conduct a detailed survey of the Giacomini site to produce an accurate topographic map of the property. The site survey can be coupled with on-site water-level measurements to produce an empirical flooding model. - Measure water level and wind regime at the Giacomini site. The water-level range is critical to determining the wetland types based on the elevation of the dairy land. Water level at Sacramento Landing, in central Tomales Bay, will also be measured for comparison. As of November 2005, we have created a GCN, produced a detailed topographic map of the Giacomini site, and collected approximately three years of water-level and wind data at the Giacomini site and over one year of usable water-level data at the Sacramento Landing pier.

California↗
USGS2011

Development of a pan-Arctic monitoring plan for polar bears: Background paper

Polar bears (Ursus maritimus), by their very nature, and the extreme, remote environment in which they live, are inherently difficult to study and monitor. Monitoring polar bear populations is both arduous and costly and, to be effective, must be a long-term commitment. There are few jurisdictional governments and management boards with a mandate for polar bear research and management, and many have limited resources. Although population monitoring of polar bears has been a focus to some degree within most jurisdictions around the Arctic, of the 19 subpopulations recognised by the IUCN/Species Survival Commission Polar Bear Specialist Group (PBSG), adequate scientific trend data exist for only three of the subpopulations, fair trend data for five and poor or no trend data for the remaining 11 subpopulations (PBSG 2010a). There are especially critical knowledge gaps for the subpopulations in East Greenland, in the Russian Kara and Laptev seas, and in the Chukchi Sea, which is shared between Russia and the United States. The range covered by these subpopulations represents a third of the total area (approx. 23 million km2) of polar bears’ current range, and more than half if the Arctic Basin is included. If we use popular terms, we know close to nothing about polar bears in this portion of their range. As summer sea-ice extent, and to a lesser degree, spring-time extent, continues to retreat, outpacing model forecasts (Stroeve et al. 2007, Pedersen et al. 2009), polar bears face the challenge of adapting to rapidly changing habitats. There is a need to use current and synthesised information across the Arctic, and to develop new methods that will facilitate monitoring to generate new knowledge at a pan-Arctic scale. The circumpolar dimension can be lost when efforts are channelled into regional monitoring. Developing and implementing a plan that harmonises local, regional and global efforts will increase our power to detect and understand important trends for polar bears, with particular emphasis on how climate warming may differentially affect populations and habitats. Current knowledge is inadequate for a comprehensive understanding of the present and future impact of climate warming and its interaction with other stressors. The cumulative effects are unknown (Laidre et al. 2008). An integrated pan-Arctic research and monitoring plan will improve the ability to detect future trends, identify the most vulnerable subpopulations and guide effective conservation. There is a need to direct attention and resources where data are deficient to understand the mechanisms that drive trends, and to facilitate more effective and timely conservation response.

Report↗
USGS2011

Playa-lake sedimentation and organic matter accumulation in an Andean piggyback basin: The recent record from the Cuenca de Pozuelos, NW Argentina

Expansive playa‐lake systems situated in high‐altitude piggyback basins are important and conspicuous components of both modern and ancient cordilleran orogenic systems. Extant playa lakes provide vital habitat for numerous endemic species, whereas sediments from these deposystems may record signals of climate change or develop natural resources over geological time. Laguna de los Pozuelos (North‐west Argentina) provides the opportunity for an actualistic sedimentological and geochemical assessment of a piggyback basin playa lake in an area of critical interest for understanding Quaternary palaeoclimate dynamics. Silty clays and diatom ooze are the dominant playa‐lake centre microfacies, with concentrations of total organic carbon and biogenic silica commonly exceeding 1·5 wt% in this sub‐environment. Elemental and stable isotopic analyses point to a mixed organic matter composition in the playa‐lake centre, with substantial contributions from algae and transported aquatic macrophytes. Bulk sediment and organic mass accumulation rates in the southern playa‐lake centre approach 0.22g cm −2 year −1 and 2.89 mg cm −2 year −1 , respectively, indicating moderately rapid deposition with negligible deflation over historic time. Playa margin facies contain higher percentages of fragmented biogenic carbonate (ostracods and charophytes) and inorganically precipitated aragonite crusts due to seasonal pumping and evaporation of ground water. Organic matter accumulation is limited along these heavily bioturbated wet and dry mud flats. Fluvial–lacustrine transitional environments, which are key waterbird habitats, are either silty terminal splay (northern axis) or sandy deltas (southern axis) containing highly oxidized and partially allochthonous organic matter. Modern analogue data from Laguna de los Pozuelos provide key insights for: (i) environmental reconstructions of ancient lake sequences; and (ii) improving facies models for piggyback basins.

Cuenca de Pozuelos↗
USGS2007

Hydrostratigraphic Framework and Selection and Correlation of Geophysical Log Markers in the Surficial Aquifer System, Palm Beach County, Florida

The surficial aquifer system is the major source of freshwater for public water supply in Palm Beach County, Florida, yet many previous studies of the hydrogeology of this aquifer system have focused only on the eastern one-half to one-third of the county in the more densely populated coastal area (Land and others, 1973; Swayze and others, 1980; Swayze and Miller, 1984; Shine and others, 1989). Population growth in the county has resulted in the westward expansion of urbanized areas into agricultural areas and has created new demands on the water resources of the county. Additionally, interest in surface-water resources of central and western areas of the county has increased. In these areas, plans for additional surface-water storage reservoirs are being made under the Comprehensive Everglades Restoration Plan originally proposed by the U.S. Army Corps of Engineers and the South Florida Water Management District (1999), and stormwater treatment areas have been constructed by the South Florida Water Management District. Surface-water and ground-water interactions in the Everglades are thought to be important to water budgets, water quality, and ecology (Harvey and others, 2002). Most of the previous hydrogeologic and ground-water flow simulation studies of the surficial aquifer system have not utilized a hydrostratigraphic framework, in which stratigraphic or sequence stratigraphic units, such as those proposed in Cunningham and others (2001), are delineated in this stratigraphically complex aquifer system. A thick zone of secondary permeability mapped by Swayze and Miller (1984) was not subdivided and was identified as only being within the Anastasia Formation of Pleistocene age. Miller (1987) published 11 geologic sections of the surficial aquifer system, but did not delineate any named stratigraphic units in these sections. This limited interpretation has resulted, in part, from the complex facies changes within rocks and sediments of the surficial aquifer system and the seemingly indistinct and repetitious nature of the most common lithologies, which include sand, shell, sandstone, and limestone. Model construction and layer definition in a simulation of ground-water flow within the surficial aquifer system of Palm Beach County utilized only the boundaries of one or two major hydrogeologic zones, such as the Biscayne aquifer and surficial aquifer system; otherwise layers were defined by average elevations rather than geologic structure or stratigraphy (Shine and others, 1989). Additionally, each major permeable zone layer in the model was assumed to have constant hydraulic conductivity with no allowance for the possibility of discrete (thin) flow zones within the zone. The key to understanding the spatial distribution and hydraulic connectivity of permeable zones in the surficial aquifer system beneath Palm Beach County is the development of a stratigraphic framework based on a consistent method of county-wide correlation. Variability in hydraulic properties in the system needs to be linked to the stratigraphic units delineated in this framework, and proper delineation of the hydrostratigraphic framework should provide a better understanding and simulation of the ground-water flow system. In 2004, the U.S. Geological Survey, in cooperation with the South Florida Water Management District, initiated an investigation to develop a hydrostratigraphic framework for the surficial aquifer system in Palm Beach County.

Scientific Investigations Map↗
USGS2016

Resource management and operations in central North Dakota: Climate change scenario planning workshop summary November 12-13, 2015, Bismarck, ND

The Scaling Climate Change Adaptation in the Northern Great Plains through Regional Climate Summaries and Local Qualitative-Quantitative Scenario Planning Workshops project synthesizes climate data into 3-5 distinct but plausible climate summaries for the northern Great Plains region; crafts quantitative summaries of these climate futures for two focal areas; and applies these local summaries by developing climate-resource-management scenarios through participatory workshops and, where possible, simulation models. The two focal areas are central North Dakota and southwest South Dakota (Figure 1). The primary objective of this project is to help resource managers and scientists in a focal area use scenario planning to make management and planning decisions based on assessments of critical future uncertainties. This report summarizes project work for public and tribal lands in the central North Dakota focal area, with an emphasis on Knife River Indian Villages National Historic Site. The report explains scenario planning as an adaptation tool in general, then describes how it was applied to the central North Dakota focal area in three phases. Priority resource management and climate uncertainties were identified in the orientation phase. Local climate summaries for relevant, divergent, and challenging climate scenarios were developed in the second phase. In the final phase, a two-day scenario planning workshop held November 12-13, 2015 in Bismarck, ND, featured scenario development and implications, testing management decisions, and methods for operationalizing scenario planning outcomes.

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