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
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
Edition: 3.01
Publication_Date: 1998
Series_Information:
Series_Name: U.S. Geological Survey Open-File Report
Issue_Identification: 98-622
Publication_Information:
Publication_Place: Reston, VA
Publisher: U.S. Geological Survey
Geospatial_Data_Presentation_Form: raster digital data
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.
Purpose: To make NURE Geochemical data available on the Internet.
Time_Period_of_Content:
Time_Period_Information:
Range_of_Dates/Times:
Beginning_Date: 1964
Ending_Date: 1995
Currentness_Reference: publication date
Status:
Progress: Complete
Maintenance_and_Update_Frequency: None planned
Spatial_Domain:
Bounding_Coordinates:
West_Bounding_Coordinate: -179.1
East_Bounding_Coordinate: -67.764
North_Bounding_Coordinate: 70.0
South_Bounding_Coordinate: 19.003
Keywords:
Theme:
Theme_Keyword_Thesaurus: none
Theme_Keyword: igneous
Theme_Keyword: pluto
Theme_Keyword: geochemistry
Place:
Place_Keyword_Thesaurus: None
Place_Keyword: United States
Temporal:
Temporal_Keyword_Thesaurus: None
Temporal_Keyword: 1999
Theme:
Theme_Keyword_Thesaurus: National Geologic Map Database Catalog themes, augmented
Theme_Keyword: 1900 - Geochemistry
Theme:
Theme_Keyword_Thesaurus: ISO 19115 Topic Categories
Theme_Keyword: geoscientificInformation
Place:
Place_Keyword_Thesaurus: Augmented FIPS 10-4 and FIPS 6-4, version 1.0
Place_Keyword: US01 = Alabama
Place_Keyword: US04 = Arizona
Place_Keyword: US05 = Arkansas
Place_Keyword: US06 = California
Place_Keyword: US08 = Colorado
Place_Keyword: US09 = Connecticut
Place_Keyword: US10 = Delaware
Place_Keyword: US11 = District of Columbia
Place_Keyword: US12 = Florida
Place_Keyword: US13 = Georgia
Place_Keyword: US16 = Idaho
Place_Keyword: US17 = Illinois
Place_Keyword: US18 = Indiana
Place_Keyword: US19 = Iowa
Place_Keyword: US20 = Kansas
Place_Keyword: US21 = Kentucky
Place_Keyword: US22 = Louisiana
Place_Keyword: US23 = Maine
Place_Keyword: US24 = Maryland
Place_Keyword: US25 = Massachusetts
Place_Keyword: US26 = Michigan
Place_Keyword: US27 = Minnesota
Place_Keyword: US28 = Mississippi
Place_Keyword: US29 = Missouri
Place_Keyword: US30 = Montana
Place_Keyword: US31 = Nebraska
Place_Keyword: US32 = Nevada
Place_Keyword: US33 = New Hampshire
Place_Keyword: US34 = New Jersey
Place_Keyword: US35 = New Mexico
Place_Keyword: US36 = New York
Place_Keyword: US37 = North Carolina
Place_Keyword: US38 = North Dakota
Place_Keyword: US39 = Ohio
Place_Keyword: US40 = Oklahoma
Place_Keyword: US41 = Oregon
Place_Keyword: US42 = Pennsylvania
Place_Keyword: US44 = Rhode Island
Place_Keyword: US45 = South Carolina
Place_Keyword: US46 = South Dakota
Place_Keyword: US47 = Tennessee
Place_Keyword: US48 = Texas
Place_Keyword: US49 = Utah
Place_Keyword: US50 = Vermont
Place_Keyword: US51 = Virginia
Place_Keyword: US53 = Washington
Place_Keyword: US54 = West Virginia
Place_Keyword: US55 = Wisconsin
Place_Keyword: US56 = Wyoming
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.
Attribute_Accuracy_Report: Refer to Open File Report 98-622
Logical_Consistency_Report: None
Completeness_Report: See Process Description below and Open File Report 98-622
Positional_Accuracy:
Horizontal_Positional_Accuracy:
Horizontal_Positional_Accuracy_Report:
Lineage:
Source_Information:
Source_Citation:
Citation_Information:
Originator: Phillip A. Baedecker
Originator: Jeffrey N. Grossman
Originator: Kim P. Buttleman
Publication_Date: 1998
Title:
National Geochemical Data Base: PLUTO Geochemical Data Base for the United States
Series_Information:
Series_Name: U.S. Geological Survey Digital Data Series
Issue_Identification: DDS-47
Geospatial_Data_Presentation_Form: Tabular digital data
Source_Time_Period_of_Content:
Time_Period_Information:
Range_of_Dates/Times:
Beginning_Date: 1964
Ending_Date: 1995
Source_Currentness_Reference: Publication date
Source_Citation_Abbreviation: PLUTO
Source_Contribution:
National Geochemical Data Base: PLUTO Geochemical Data Base for the United States
Type_of_Source_Media: CD-ROM
Process_Step:
Process_Description:
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).
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.
Metadata_Reference_Information:
Metadata_Date: 19990226
Metadata_Contact:
Contact_Information:
Contact_Person_Primary:
Contact_Person: Tom Kress
Contact_Organization: U.S. Geological Survey
Contact_Address:
Address_Type: mailing and physical address
Address: 12201 Sunrise Valley Dr.
City: Reston
State_or_Province: VA
Postal_Code: 20192
Country: USA
Contact_Voice_Telephone: 703-648-6184
Contact_Electronic_Mail_Address:thkress@usgs.gov
Metadata_Standard_Name: Content Standard for Digital Geospatial Metadata
Metadata_Standard_Version: FGDC-STD-001-1998
This page is <http://geo-nsdi.er.usgs.gov/metadata/open-file/98-622/metadata.html> How other people discovered this page
Generated by mp version 2.9.5 on Fri Oct 19 13:36:55 2007