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National Geochemical Atlas: The Geochemical Landscape of the Conterminous United States Derived from Stream Sediment and other Solid Sample Media Analyzed by the National Uranium Resource Evaluation (NURE) Program

Metadata also available as - [Outline] - [Parseable text] - [DIF]

Frequently-anticipated questions:

What does this data set describe?

Title:
National Geochemical Atlas: The Geochemical Landscape of the Conterminous United States Derived from Stream Sediment and other Solid Sample Media Analyzed by the National Uranium Resource Evaluation (NURE) Program
Abstract:
This CD presents maps derived from a subset of the National Uranium Resource Evaluation (NURE) Hydrogeochemical and Stream Sediment Reconnaissance (HSSR) data. Approxiamately 260,000 samples were analyzed in the continental U.S. and consisted of solid samples, including stream, lake, pond, spring, and playa sediments, and soils. Data for eleven elements were analyzed and included on this release of the National Geochemical Atlas CD: Na, Ti, Fe, Cu, Zn, As, Ce, Hf, Pb, Th, and U. The National Uranium Resource Evaluation (NURE) program of the Department of Energy (DOE) collected a vast amount of chemical data on sediment, soil, and water samples from the United States in the late 1970's and early 1980's. This element of the NURE program was known as the Hydrogeochemical and Stream Sediment Reconnaissance (HSSR). The NURE HSSR data have long been available to the public in a variety of formats, ranging from the original paper reports produced by the DOE (see Averett, 1984), to comprehensive digital releases on CD-ROM by the U.S. Geological Survey in the last few years (Hoffman and Buttleman, 1994; 1996), to digital releases on the Internet of reformatted and cleaned data (Smith, 1998). While these publications remain the best sources of the complete, primary data, and are accompanied by documentation of the sampling protocols, sample characteristics, and analytical methods, they are difficult to use for geochemical research, especially when the study area covers a wide area of the United States. This publication is intended to allow the rapid visualization of the geochemical landscape of the United States using the NURE HSSR data. Here, the user is relieved of the responsibility of selecting and processing the raw data; this was done in the preparation of the CD. A powerful geographic-information system (GIS) tool, the ArcView program of Environmental Systems Research Institute, Inc. (ESRI), is provided to allow one to probe and manipulate the processed NURE data. Within the ArcView environment, multiple presentations of the NURE are provided, ranging from color-coded point maps, to bitmap-images on a national scale, to interpreted maps based on geologic and hydrologic units. Because the NURE HSSR data have been processed by the author for the production of this CD, the user must use a degree of caution in interpreting the maps produced here, and in using the data files found on the disc. One must understand the methods used in deriving the data on this CD in order to judge the significance of any particular map or data feature. Fortunately, the raw data used in the production of this CD are available in digital form (Hoffman and Buttleman, 1996), for examination by sophisticated users.
  1. How should this data set be cited?

    Grossman, Jeffrey N. , 1998, National Geochemical Atlas: The Geochemical Landscape of the Conterminous United States Derived from Stream Sediment and other Solid Sample Media Analyzed by the National Uranium Resource Evaluation (NURE) Program: U.S. Geological Survey Open-File Report 98-622, U.S. Geological Survey, Reston, VA.

    Online Links:

  2. What geographic area does the data set cover?

    West_Bounding_Coordinate: -179.1
    East_Bounding_Coordinate: -67.764
    North_Bounding_Coordinate: 70.0
    South_Bounding_Coordinate: 19.003

  3. What does it look like?

  4. Does the data set describe conditions during a particular time period?

    Beginning_Date: 1964
    Ending_Date: 1995
    Currentness_Reference: publication date

  5. What is the general form of this data set?

    Geospatial_Data_Presentation_Form: raster digital data

  6. How does the data set represent geographic features?

    1. How are geographic features stored in the data set?

      This is a Raster data set. It contains the following raster data types:

      • Dimensions, type Pixel

    2. What coordinate system is used to represent geographic features?

      The map projection used is Albers Conical Equal Area.

      Projection parameters:
      Standard_Parallel: 29 30 00
      Longitude_of_Central_Meridian: -96.0
      Latitude_of_Projection_Origin: 23.0
      False_Easting: 0
      False_Northing: 0

      Planar coordinates are encoded using row and column
      Planar coordinates are specified in kilometer

      The horizontal datum used is North American Datum of 1927.
      The ellipsoid used is Clarke 1866.
      The semi-major axis of the ellipsoid used is 6370997 meters.
      The flattening of the ellipsoid used is 1/294.98.

  7. How does the data set describe geographic features?

    Entity_and_Attribute_Overview:
    Entity_and_Attribute_Detail_Citation: Open File Report 98-622

Who produced the data set?

  1. Who are the originators of the data set? (may include formal authors, digital compilers, and editors)

  2. Who also contributed to the data set?

  3. To whom should users address questions about the data?

    Jeffrey N. Grossman
    U.S. Geological Survey
    12201 Sunrise Valley Dr.
    Reston, VA 20192
    USA

    703 648-6184 (voice)
    jgrossman@usgs.gov

Why was the data set created?

To make NURE Geochemical data available on the Internet.

How was the data set created?

  1. From what previous works were the data drawn?

    PLUTO (source 1 of 1)
    Baedecker, Phillip A. , Grossman, Jeffrey N. , and Buttleman, Kim P. , 1998, National Geochemical Data Base: PLUTO Geochemical Data Base for the United States: U.S. Geological Survey Digital Data Series DDS-47.

    Type_of_Source_Media: CD-ROM
    Source_Contribution:
    National Geochemical Data Base: PLUTO Geochemical Data Base for the United States

  2. How were the data generated, processed, and modified?

    Date: 1998 (process 1 of 1)
    The backbone of this CD is a series of DBase (DBF) files, each containing the point data for a single element in a set of solid (sediment) samples from the NURE HSSR program. All of the images and map coverages on the CD are derived from these DBF files. This section outlines the steps used in creating these files. The starting point for data processing on this CD is the set of quadrangle-by-quadrangle DBF files of NURE HSSR data found in Hoffman and Buttleman (1996). Note that these files are not the raw NURE data, but are themselves processed from the original digital files (on tape) produced by DOE. Indeed, the DOE tapes are also not the true raw data from the program, as there was a manual data-processing step to transfer data from paper reports. 308 quadrangle files (covering the continental U.S.) from Hoffman and Buttleman (1996) contained data for stream, lake, or spring sediments, and a subset of 43 of these files also contained data for soils (Table 1). qqqRecords covering these sample media were selected for inclusion in this CD. Most of the selection of records from the original DBF files, and other primary data extraction tasks were done with the Paradox database program. The steps in this procedure were as follows: Records were extracted from the quadrangle DBF files for the appropriate sample media using one or more of the field codes listed in Table 2. (See Hoffman and Buttleman, 1994, for explanation of codes.) After surveying each file (through a series of Paradox queries), a new query was constructed that extracted all records for stream sediments (wet and dry), lake and pond sediments (including dry lakes), spring sediments, and soils. Data fields were chosen from the selected records for further processing. These included several label fields, the sample-type fields listed in Table 2, the geographic coordinates, fields for the 54 chemical elements appropriate for solid samples (Ag, Al, As, Au, B, Ba, Be, Bi, Ca, Cd, Ce, Co, Cr, Cs, Cu, Dy, Eu, Fe, Hf, Ho, K, La, Li, Lu, Mg, Mn, Mo, Na, Nb, Nd, Ni, P, Pb, Pt, Rb, Ru, Sb, Sc, Se, Si, Sm, Sn, Sr, Ta, Tb, Th, Ti, U, V, W, Y, Yb, Zn, Zr), and 5 miscellaneous fields that contain chemical data (CONCN01 through CONCN05). A Paradox query extracted these fields, and all other data were discarded (including things like stream characteristics, contamination codes, various labels, and fields not used for solid sample media). Most chemical data in the quadrangle DBF files are stored in parts-per-billion (ppb). Paradox was used to convert each field into a more appropriate unit: parts-per-million (ppm) for trace elements, and wt.% for major elements (Al, Ca, Fe, K, Mg, and Na). Many samples were analyzed by more than one laboratory, or by more than one method. In these cases, there are multiple records in the quadrangle DBF files for an individual sample location, each with analyses for different elements. These records were found and combined into a single record. Paradox was used to sort the records by latitude and longitude. A temporary DBF file was generated, and read by a DOS FORTRAN program, ECLEAN, written by the author (unpublished). This program searched for consecutive records that had identical or nearly identical geographic coordinates (within 0.0005 degrees, or ~50 m, of each other). These were assumed to be the same sample, as round-off errors sometimes affected the 4th decimal place. ECLEAN then combined these records, element by element, into a single new record. In the few cases where data for the same element was present in two or more records, the highest value was arbitrarily chosen. This process also had the effect of consolidating samples actually collected as duplicates at a single location into single records. ECLEAN also eliminated records with no chemical data (and there were many of these). The program then created a new DBF file with the consolidated data. At the beginning of this processing stage, the 308 original quadrangle DBF files have been reduced to 308 new DBF files containing only the geographic and chemical-element fields of the sediment and soil data, without any duplicate or blank records. Major systematic problems, as discussed above, have been corrected. The following processing steps were used to find and correct additional problems in the datasets, to search for regional inconsistencies in the data, and to establish the usefulness of data reported as upper limits (e.g.,<10 ppm). The reduced DBF files were surveyed with a DOS FORTRAN program, also written by the author, called GRIDPLOT. This program reads in multiple DBF files, and produces a simple, color, gridded map of the data for one element on the computer screen. It is extremely efficient, and allows the rapid visualization of the data (all 308 files can be read, and a plot generated on a 200 MHz PentiumPro PC in about 1 minute). Systematic errors that were not found during primary data processing can be seen visually, as discontinuities in the colored map. In some cases, these could be traced to systematic errors in the quadrangle DBF files, especially errors in the position of decimal points. These were corrected by repeating the primary processing for the affected quadrangle. Other discontinuities are caused by analytical errors, and are handled in step 2.2.
    In some areas, generally in the western U.S., one or more quadrangles, or parts of quadrangles, would appear to be discontinuous with adjacent quadrangles for a given element, when viewed with GRIDPLOT. In many such instances, a good case can be made that there is a systematic analytical error (i.e., an accuracy problem, probably due to different analytical methods or interlaboratory calibration problems) across the discontinuity. The best argument for the occurrence of this type of error is that regional chemical trends are seen on both sides of the discontinuity, and the application of a simple correction factor can make the data appear continuous. In these cases, a correction factor is supplied to GRIDPLOT for the affected areas, and the factor is adjusted until the gridded map appears smooth and continuous. Such corrections can be displayed graphically in ArcView, by examining the Data Processing themes for each element (see below). In other cases, either no correction factor can correct the discontinuity, or regional trends are absent in certain quadrangles and the data appear to be random. Such data were deleted from this CD, and the Data Processing theme will show a correction factor of zero (see, as a good example, the hafnium data in ArcView). A negative concentration of an element in the quadrangle DBF files indicates that the value is an upper limit (e.g., -10 implies <10 ). These values present a special problem in creating map coverages of geochemical data. The philosophy adopted here is a simple one: steps are taken to ensure that all upper limits fall within the lowest interval in the final map legend, and thus are known to be correctly categorized. First, two histograms are prepared for each element, one showing the concentration range of unqualified data, the other showing only upper limits For most elements, the vast majority of the data fall in the first histogram, and markers are inserted into this plot showing the values of every 5th percentile (for reference). The second histogram is displayed below the first, and compared visually. The strategy is to select a cutoff value below which upper limits are to be retained, such that they do not affect the accuracy of the map. Above this cutoff, upper limits are deleted from the final dataset. In the case shown in Fig. 1, it would be possible to construct maps using a color legend that has as its lowest interval the lowest 5th percentile of the data. Upper limits with values of <2 ppm fall unambiguously within this lowest color interval, and can be merged into the final dataset without affecting the appearance or accuracy of the map; in practice, the < is dropped, and the value multiplied by 0.5. However, those upper limits with values of <6 ppm could have real values (had they be measured more precisely) that fall anywhere within the lowest 30% of the concentration distribution. Such values cannot be assigned with certainty to the correct color interval in the map legend, and are simply deleted. The graphical result of deletions of this type may be small holes in the map where grid cells could not be assigned real values. Table 3 shows the values of these cutoffs for each of the elements compiled on this CD.
    Once the data are leveled, upper limit cutoffs are established, and areas of bad data are identified, the GRIDPLOT program is run again to utilize its secondary function, which is to extract values for a single element from all 308 processed quadrangle DBF files. For the special case of uranium, GRIDPLOT was programmed to make choices about which data field to use for the final value. Uranium is typically stored in one of five fields in the original quadrangle DBF files: one labeled as CONU , the others as CONCN01, CONCN02, CONCN05, and CONUDN. The CONC05 field was given priority over the CONU field if both were filled, and data in the CONCN01 and CONCN02 fields were used in the absence of data in the first two fields. The CONUDN field (U by delayed neutron) was only coded in few percent of the samples (in only 9 quadrangles), but these data were not used here. The output from this data processing step is a series of elemental DBF files of useable NURE data.
    Several major errors in the NURE HSSR data were identified and corrected during the above data-processing steps. These errors are present in the original DBF files and composite database of Hoffman and Buttleman (1994; 1996). The errors will be corrected in the a new database (Smith, 1998), but as of this time only a small part of the United States is covered by this. The data survey conducted for each quadrangle DBF file in step 1.1 uncovered a block of stream-sediment samples miscoded as stream water in seven quadrangles in the northeastern U.S. (Boston, Glen Falls, Lake Champlain, Lewiston, Newark , Scranton, and Williamsport). These records were altered to give them the correct coding prior to any data processing. In ~30,000 samples collected and analyzed by Oak Ridge Gaseous Diffusion Plant (ORGDP) and tabulated in the quadrangle DBF files, major elements (Al, Ca, Fe, K, Mg, and Na) plus As and Se were all tabulated incorrectly in units other than ppb. Over 70 quadrangles contain data affected by this problem. These records can be identified from the lack of coding in the SAMPTYP field, and a value of 4 coded in the SAMPMDC field. These problems were corrected as a group. A group of ~15,000 records found in several dozen quadrangles in the western U.S. (samples analyzed but not collected by ORGDP) also contain major element data in ppm instead of ppb, although trace elements are all coded correctly. Most of these are coded as soils (SAMPTYP=59), talus (SAMPTYP=62), or uncoded in this field (SAMPTYP=blank), and all have a value of M coded in the LTYPC field, which stands for sediment. These were also corrected by special handling. Themes with names of the form Grid: Cu are elemental concentration maps, produced from a gridded version of the point data. These bitmap files (Tiff) are based on grids made with the MINC program of Webring (1981), which employs a minimum curvature interpolation of the point data to create a smooth surface. The grid-cells used were 2 km on each side. Following the gridding operation, the program GCLR (unpublished, by R. W. Simpson, USGS, Menlo Park, Calif.) was used to produce a color-shaded relief map. The color-scheme of these maps is similar to that used in the point-data themes, as it is based upon the distribution of the underlying point data. Here, seven intervals are used, corresponding to the lowest 40th, the 40th-80th, the 80th-90th, the 90th-95th, the 95th-98th, the 98th-99th, and the 99th-100th percentiles. The legends for all these maps, showing the actual concentration values corresponding to each color interval, are shown in a special view called Gridded Elemental Map Legends. Gridded elemental map legends. This view contains an image showing the concentrations of each element corresponding to each color interval in the gridded elemental maps. Taking just the left side of this legend as an example: the gridded elemental map shown in the Arsenic Geochemistry view has its dark blue color corresponding to <2.4 ppm As, light blues representing 2.4 to 5.2 ppm, greens representing 5.2 to 7.6 ppm As, etc., up to magenta representing >22 ppm As. Note that because the grid is actually a shaded-relief rendition of the data, each color grades somewhat from high saturation (left side of color bar) to low saturation (right side of color bar).

    Person who carried out this activity:

    Jeffrey N. Grossman
    U.S. Geological Survey
    12201 Sunrise Valley Dr.
    Reston, VA 20192
    USA

    703-648-6184 (voice)
    jgrossman@usgs.gov

  3. What similar or related data should the user be aware of?

How reliable are the data; what problems remain in the data set?

  1. How well have the observations been checked?

    Refer to Open File Report 98-622

  2. How accurate are the geographic locations?

  3. How accurate are the heights or depths?

  4. Where are the gaps in the data? What is missing?

    See Process Description below and Open File Report 98-622

  5. How consistent are the relationships among the observations, including topology?

    None

How can someone get a copy of the data set?

Are there legal restrictions on access or use of the data?

Access_Constraints: None
Use_Constraints:
The U.S. Geological Survey makes no warranties related to the accuracy of the data and users are required to determine the suitability of use for any particular purpose.

  1. Who distributes the data set? (Distributor 1 of 1)

    Jeff Grossman
    USGS
    954 National Center
    Reston, VA 20192
    USA

    703-648-6184 (voice)
    jgrossman@usgs.gov

  2. What's the catalog number I need to order this data set?

    nure.zip

  3. What legal disclaimers am I supposed to read?

    The U.S. Geological Survey (USGS) provides this vector data as is. The USGS makes no guarantee or warranty concerning the accuracy of information contained in the raster data. The USGS further makes no warranties, either expressed or implied as to any other matter whatsoever, including, without limitation, the condition of the product, or its fitness for any particular purpose. The burden for determining fitness for use lies entirely with the user. Although this data has been processed successfully on computers at the USGS, no warranty, expressed or implied, is made by the USGS regarding the use of this data on any other system, nor does the fact of distribution constitute or imply any such warranty.

  4. How can I download or order the data?

Who wrote the metadata?

Dates:
Last modified: 26-Feb-1999
Metadata author:
Tom Kress
U.S. Geological Survey
12201 Sunrise Valley Dr.
Reston, VA 20192
USA

703-648-6184 (voice)
thkress@usgs.gov

Metadata standard:
Content Standard for Digital Geospatial Metadata (FGDC-STD-001-1998)

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