Sandstone copper assessment of the Chu-Sarysu Basin, central Kazakhstan

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What does this data set describe?

Title:
Sandstone copper assessment of the Chu-Sarysu Basin, central Kazakhstan
Abstract:
Mineral resource assessments represent a synthesis of available information to estimate the location, quality, and quantity of undiscovered mineral resources in the Earth's crust. A probabilistic mineral resource assessment of undiscovered sandstone- copper deposits within the Upper Paleozoic Chu-Sarysu Basin in central Kazakhstan was done as a contribution to a global assessment of mineral resources conducted by the U.S. Geological Survey. The purpose of this study was to (1) delineate permissive areas (tracts) for undiscovered sandstone-hosted copper deposits within 2 km of the surface in this area to be presented at a scale of 1,000,000, (2) provide a database of known sandstone copper deposits and significant prospects in this area, (3) estimate numbers of undiscovered deposits within these permissive tracts at several levels of confidence, and (4) provide probabilistic estimates of amounts of copper (Cu), silver (Ag), and mineralized rock that could be contained in undiscovered deposits within each tract. The assessment was conducted using a three-part form of mineral resource assessment based on mineral deposit models (Singer, 1993 Singer and Menzie, 2010). Delineation of permissive tracts was based on the distribution of a Carboniferous, oxidized non-marine clastic (red bed) stratigraphic sequence that lies between overlying Permian and underlying Devonian evaporite-bearing sequences. Using subsurface information on the extent and depth of this red bed sequence and on structural features that divide the basin into sub-basins, we subdivide the continuous permissive area into four permissive tracts. Structure contour maps, mineral-occurrence databases, drill hole lithologic logs, geophysical maps, soil geochemical maps, locations of producing gas fields, and evidence for former gas accumulations were considered in conjunction with descriptive deposit models and grade and tonnage models to guide our estimates of undiscovered deposits in each tract. The four permissive tracts delineated in this assessment are structural sub-basins of the Chu-Sarysu Basin and range in size from 750 km2 to 65,000 km2. Probabilistic estimates of numbers of undiscovered sandstone copper deposits were made for the 4 tracts. Using these probabilistic estimates, Monte Carlo simulation was used to estimate the amount of contained metals for each tract, which serve as the basis for estimates of their metal endowment. In this assessment we estimate that a mean of 26 undiscovered deposits occur within the Chu-Sarysu Basin containing an arithmetic mean estimate of 21.5 million (or more) metric tons of copper, in addition to the 7 known deposits that contain identified resources of 27.6 million metric tons of copper. Sixty percent of the estimated mean undiscovered copper resources are associated with the two permissive tracts that contain the identified resources; the remaining estimated resources are associated with the two tracts with no known deposits. For the 3 tracts with 95 percent of the estimated mean undiscovered copper resources, the probability that each tract contains its estimated mean or greater is about 40 percent. For the southern tract with 5 percent of the estimated mean undiscovered copper resources, the probability that it contains that amount or greater is 25 percent. This report includes a brief overview of the geologic framework of the Chu-Sarysu Basin and its sandstone copper deposits, a description of the assessment process, a summary of results, and appendixes. Appendixes A through D contain summary information of each tract, as follows: location, the geologic feature assessed, the rationale for tract delineation, tables and descriptions of known deposits and significant prospects, exploration history, model selection, rationale for the estimates, assessment results, and references. The accompanying geodatabase files (feature classes) provide permissive tract outlines, assessment results, and data for deposits and prospects in a GIS format (Appendix F).
Supplemental_Information:
The U.S. Geological Survey is conducting a cooperative international project to assess the world's undiscovered nonfuel mineral resources. The Global Mineral Resource Assessment Project (GMRAP) is a research project that will develop and test methods of assessing the undiscovered mineral resources of the terrestrial earth. The primary objectives of the project are to outline the principal areas in the world that have potential for selected undiscovered mineral resources and to estimate the probable amounts of those mineral resources to a depth of 1-2 kilometers (0.6-1.2 miles) below the earth's surface. The project will initially undertake global assessments of copper, platinum-group metals, and potassium (or potash) resources (<http://pubs.usgs.gov/fs/fs053-03/fs053-03.pdf>).
A probabilistic mineral resource assessment of undiscovered (sediment-hosted) sandstone - copper deposits within the Upper Paleozoic Chu-Sarysu Basin in central Kazakhstan was undertaken as a contribution to the global assessment of mineral resources (GMRAP) currently being conducted by the U.S. Geological Survey.
  1. How should this data set be cited?

    Box, Stephen E. , Syusyura, Boris, Hayes, Timothy S. , Taylor, Cliff D. , Zientek, Michael L. , Hitzman, Murray W. , Seltmann, Reimar, Chechetkin, Vladimir, Dolgopolova, Alla, Cossette, Pamela M. , and Wallis, John C. , 2011, Sandstone copper assessment of the Chu-Sarysu Basin, central Kazakhstan: Scientific Investigations Report 2010-5090-E, U.S. Geological Survey, Menlo Park, California.

    Online Links:

  2. What geographic area does the data set cover?

    West_Bounding_Coordinate: 66.198100
    East_Bounding_Coordinate: 73.761778
    North_Bounding_Coordinate: 48.365624
    South_Bounding_Coordinate: 42.600760

  3. What does it look like?

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

    Calendar_Date: 2012
    Currentness_Reference: current

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

    Geospatial_Data_Presentation_Form: report and vector digital data

  6. How does the data set represent geographic features?

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

      This is a Vector data set. It contains the following vector data types (SDTS terminology):

      • G-polygon

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

      Horizontal positions are specified in geographic coordinates, that is, latitude and longitude. Latitudes are given to the nearest 0.000000. Longitudes are given to the nearest 0.000000. Latitude and longitude values are specified in Decimal degrees.

      The horizontal datum used is D_WGS_1984.
      The ellipsoid used is WGS_1984.
      The semi-major axis of the ellipsoid used is 6378137.000000.
      The flattening of the ellipsoid used is 1/298.257224.

  7. How does the data set describe geographic features?

    CS_Assessed_Tracts
    ESRI File Geodatabase FEATURE CLASS - describes assessed mineral resource tracts (polygon features) which are permissive for sediment-hosted copper (Source: Singer, D.A., 1993, Basic concepts in three-part quantitative assessments of undiscovered mineral resources: Nonrenewable Resources, v. 2, no. 2, p. 69-81.)

    TRACT_ID
    User-defined, unique identifier assigned to permissive tract (Source: GMRAP)

    CODED_ID
    Coded, unique identifier assigned to permissive tract (Source: GMRAP)

    TRACT_NAME
    Informal (author-defined) name of permissive tract (Source: GMRAP)

    UNREGCODE
    Three digit UN code for the region that underlies most of the permissive tract. (Source: UN Standard Country or Area Codes for Statistical Use: Composition of macro geographical (continental) regions, geographical sub-regions, and selected economic and other groupings (<http://unstats.un.org/unsd/methods/m49/m49regin.htm>))

    COUNTRY
    Country(ies) in which permissive tract is located (Source: ISO 3166-1 country_name)

    COMMODITY
    Primary commodity being assessed (Source: Cu)

    DEP_TYPE
    Name of the deposit type assessed (Source: sediment-hosted copper)

    GT_MODEL
    Grade-tonnage model used for the undiscovered deposit estimate (Source: Singer, D.A., Berger, V.I., and Moring, B.C., 2008, Porphyry copper deposits of the world: database, map, and grade and tonnage models, 2008: U.S. Geological Survey Open-File Report 2008-1155, 45 p., accessed January 15, 2009, at <http://pubs.usgs.gov/of/2008/1155/>.)

    GEOLOGY
    Geologic feature assessed (Source: GMRAP)

    AGE
    Age of geologic feature assessed (Source: Geologic time terms in USGS Divisions of geologic time (Suggestions to Authors fig. 15, p. 59); Geological Society of America 1999 Geologic time scale; or International Commission on Stratigraphy Geologic Time Scale 2004)

    ASMT_DATE
    Year assessment was conducted (Source: GMRAP)

    ASMT_DEPTH
    Maximum depth beneath the Earth's surface used for the assessment, in kilometers. (Source: GMRAP)

    EST_LEVELS
    The set of percentile (probability) levels at which undiscovered deposit estimates were made (Source: GMRAP)

    N90
    Estimated number of deposits associated with the 90th percentile (90 percent chance of at least the indicated number of deposits). (Source: GMRAP)

    N50
    Estimated number of deposits associated with the 50th percentile (50 percent chance of at least the indicated number of deposits). Values for N90 <or=N50 <or= N10<or= N05<or= N01 (Source: GMRAP)

    N10
    Estimated number of deposits associated with the 10th percentile (10 percent chance of at least the indicated number of deposits). Values for N90 <or = N50 <or= N10<or= N05 <or=N01 (Source: GMRAP)

    N05
    Estimated number of deposits associated with the 5th percentile (5 percent chance of at least the indicated number of deposits). (Source: GMRAP)

    N01
    Estimated number of deposits associated with the 1st percentile (1 percent chance of at least the indicated number of deposits). (Source: GMRAP)

    N_EXPECTED
    Expected (mean) number of deposits (Source: N_Expected = (0.233*N90) + (0.4*N50) + (0.225*N10) + (0.045*N05) + (0.03*N01))

    S
    Standard deviation (Source: s = 0.121 - (0.237*N90) - (0.093*N50) + (0.183*N10) + (0.073*N05) + (0.123*N01))

    CV_PERCENT
    Coefficient of variance, in percent (Source: Cv = (s/N_Expected) * 100)

    N_KNOWN
    Number of known deposits in the tract (Source: GMRAP)

    N_TOTAL
    Total number of deposits (Source: N_total = N_Expected + N_Known)

    AREA_KM2
    Area of permissive tract, in square kilometers (Source: GMRAP)

    DEPDENSITY
    Deposit density (total number of deposits per square kilometer). (Source: DepDensity = N_total/Area_km2)

    DEPDEN10E5
    Deposit density per 100,000 square kilometers (Source: DepDen10E5 = DepDensity*100,000)

    ESTIMATORS
    Names of people on the estimation team (Source: GMRAP)

    NOTES
    Notes or comments (Source: GMRAP)

    CS_Deposits_Prospects_AreasPrognosticResourceEstimate
    ESRI File Geodatabase FEATURE CLASS - describes deposits, prospects and areas that have prognostic resource estimates (point features) used to delineate the extent of the assessed mineral resource tracts (polygon features) which are permissive for sediment-hosted copper (Source: GMRAP)

    GMRAP_ID
    Unique record identifier. Numbers 1 through 710 agree with the DepositID field in Singer and others (2008). Numbers starting with 1000 are from the SE Asia-China-Mongolia assessment (Peters and Nokleberg). Numbers starting with 3000 are from the Mexico assessment (Hammarstrom). Note that the DepositID field in Singer and others (2008) was called MapId in Singer and others (2005); however, some records were deleted, updated, or reclassified in the 2008 release. (Source: GMRAP)

    TRACT_ID
    GMRAP user-defined, unique identifier assigned to permissive tract in which deposit or prospect is located (Source: GMRAP)

    CODED_ID
    GMRAP coded identifier for the permissive tract in the GMRAP permissive tract GIS database (Source: GMRAP)

    TRACT_NAME
    GMRAP user-defined informal tract name (Source: GMRAP)

    GROUP_NAME
    Group name of multiple sites (Source: GMRAP)

    NAME
    Name or identity (where known) of prospect or deposit site (Source: Author(s))

    NAME_OTHER
    Other names used for the site (Source: GMRAP)

    INCLUDES
    Names of deposits that have been combined with the primary deposit as a result of the 2-km aggregation rule used for calculating grades and tonnages (Source: GMRAP)

    BELONGS_TO
    Name of district, belt, trend, etc. (Source: GMRAP)

    TYPE
    Mineral deposit type (Source: GMRAP)

    SUBTYPE
    SUBTYPE: For the sediment-hosted copper type, deposits and prospects may be classified as the general type or a subtype may be specified in the reference cited. Subtype may be based on reductant and environment or may be based on geologic indication. (Source: GMRAP)

    ASSOC_TYPE
    Associated deposit types (Source: GMRAP)

    SITESTATUS
    Prospect or Deposit (Prospect if no grade and tonnage values provided. Deposit if it has grade and tonnage) (Source: GMRAP)

    SITESTATI
    (Source: GMRAP)

    SITESTATII
    (Source: GMRAP)

    DEVSTATUS
    Development Status - the nature of operations at the time the deposit record was entered or this field was last modified. Values are: Occurrence, Prospect, Producer, Past Producer, Unknown. The category definitions are as follows: Occurrence - Ore mine (Source: GMRAP)

    LATITUDE
    Latitude in decimal degrees. -90.00000 to 90.00000. Negative south of the equator (Source: GMRAP)

    LONGITUDE
    Longitude in decimal degrees. -180.00000 to 180.00000. Negative east of the Greenwich meridian (Source: GMRAP)

    CODE_CNTRY
    Country code (from Singer and others, 2005) (Source: GMRAP)

    COUNTRY
    Country(countries) in which site is located (Source: GMRAP)

    STATE_PROV
    State or province in which site is located (Source: GMRAP)

    BASIN_USGS
    ID for oil and gas basin from USGS Energy assessments (Source: GMRAP)

    BASIN_AGI
    Value of BASINGEO_I from basins.shp in AGI Datapages 459 (Source: GMRAP)

    BASINTELUS
    Value of BASIN_ID from Tellus_Sedimentary_Basins_Layer.shp (Source: GMRAP)

    AGE_MA
    Age in millions of years before present. Age is average for geologic era, period, or epoch listed (Source: GMRAP)

    AGE_METHOD
    Method for absolute age or "mid-point" if value is the midpoint of the age range (or geologic time unit) (Source: GMRAP)

    AGE_RANGE
    Age of host rock in standard divisions of geologic time (Source: GMRAP)

    AGE_REF
    Short reference for age information (Source: GMRAP)

    COMM_MAJOR
    Major commodities in decreasing order of economic importance. Use chemical symbols for commodities (Source: GMRAP)

    COMM_MINOR
    Minor commodities (byproducts, coproducts) in decreasing order of importance (Source: GMRAP)

    COMM_TRACE
    Trace commodities (Source: GMRAP)

    TONNAGE_MT
    Ore tonnage in millions of metric tons (Source: GMRAP)

    CU_PCT
    Average copper grade in weight percent (Source: GMRAP)

    CO_PCT
    Average cobalt grade in weight percent (Source: GMRAP)

    AU_G_T
    Average gold grade in ppm (=grams per ton) (Source: GMRAP)

    AG_G_T
    Average silver grade in ppm (=grams per ton) (Source: GMRAP)

    CON_CU_T
    Million metric tons of contained copper (Source: GMRAP)

    COMMENTS
    Miscellaneous comments (Source: GMRAP)

    HOSTROCKS
    Simplified lithologic description of host rocks (Source: GMRAP)

    UNIT
    Geologic map unit in which site is located (Source: GMRAP)

    FOOTWALL
    Rock types of footwall rocks (Source: GMRAP)

    HANGWALL
    Rock types of hangingwall rocks (Source: GMRAP)

    MINERALOGY
    Ore and gangue minerals in approximate order of abundance (Source: GMRAP)

    SOURCE
    Data table source (Source: GMRAP)

    UPDATER
    Last editor or updater of record (Source: GMRAP)

    UPDATE
    Date LastEditor edited, changed or added data (Source: GMRAP)

    ED_COMMENT
    Editor's comments (Source: GMRAP)

    REF_SHORT1
    Short reference (Source: GMRAP)

    REF_SHORT2
    Short reference (Source: GMRAP)

    GEOLPROV
    (Source: GMRAP)

    TCTNIC_SET
    (Source: GMRAP)

    COMPLEX
    (Source: GMRAP)

    GRADE_LEVL
    (Source: GMRAP)

    ENRICHMENT
    (Source: GMRAP)

    OTHER
    (Source: GMRAP)

    DEPTYPE_OLD
    (Source: GMRAP)

    FORM
    (Source: GMRAP)

    CS_Assessed_Tracts_Subunits
    ESRI File Geodatabase FEATURE CLASS - describes areas specific to and contained within the encompassing assessed tract which are here identified as tract subunits. Subunit here indicates an area that is judged to be more prospective and has had some exploration activities. Subunits are represented spatially by an approximate extent and are not individually assessed. (Source: Syusyura, Boris, Box, S.E., and Wallis, J.C., 2010, Spatial databases of geological, geophysical, and mineral resource data relevant to sandstone-hosted copper deposits in central Kazakhstan: U.S. Geological Survey Open-File Report 2010-1124, 4 p. and databases, accessed January 7, 2011 at <http://pubs.usgs.gov/of/2010/1124/>.)

    TRACT_ID
    User-defined, unique identifier assigned to permissive tract (Source: GMRAP)

    CODED_ID
    Coded, unique identifier assigned to permissive tract (Source: GMRAP)

    TRACT_NAME
    Informal (author-defined) name of permissive tract (Source: Box, 2012)

    AREA_KM2
    Area of permissive tract, in square kilometers (Source: GMRAP)

    ASSESSMENT_SUBUNIT
    Alphanumeric identification of assessment subunit (Source: Box, 2012)

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?

    Michael L. Zientek and Jane M. Hammarstrom provided a seemingly endless font of patience, guidance and oversight. Stephen E. Box provided the fundamental scientific and geological analysis of disparate data sources, many of which were acquired from the Centre for Russian and Central EurAsian Mineral Studies (CERCAMS) National Museum of History, London and Economic Consulting Ltd., Almaty, Kazakhstan. Boris Syusyura (Economic Consulting Ltd., Almaty, Kazakhstan) kindly shared data and provided personal interpretations to assist in the difficulties that are inherent in multi-national cooperative efforts. Timothy S. Hayes provided significant insight into processes that are responsible for sediment-hosted copper deposits, such as those assessed in this report. Cliff D. Taylor similarly provided insight into the properties and distribution of sediment-hosted copper deposits. Murray W. Hitzman provided invaluable expertise and guidance throughout the actual assessment process (Vancouver, 2009) in order to assure that the assessors were adequately informed and that the assessment outcomes were not unrealistic. Reimar Seltmann provided interpretation and guidance with respect to the CERCAMS data contribution and the assessment process. Vladimir Chechetkin provided a life-time of profound, on-the-ground, hands-on knowledge of the Kazakh sediment-hosted copper potential. Alla Dolgopolova provided real-time, greatly appreciated translation for the USGS scientists when our Russian-speaking guests exhausted their English-speaking abilities. Furthermore, Ms. Dolgopolova contributed her geologic and interpretative expertise (CERCAMS) in order to facilitate the assessment. Pamela M. Cossette provided GIS and editorial support. John C. Wallis (USGS contractor) provided data processing particularly in the great need for extensive translation efforts.
    In addition, Heather Parks (USGS contractor) assisted with graphics. USGS colleagues Jane Hammarstrom, Greta Orris, Mark Cocker, and Greg Spanski served as the assessment oversight committee to review the preliminary results. USGS colleagues Rich Goldfarb, Tom Moore, and Connie Dicken provided helpful and timely technical reviews of the final report. USGS colleague Connie Dicken provided a helpful technical review of the GIS data accompanying the final report. Jim Bliss (USGS) provided help on assessment methods.

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

    Stephen E. Box
    U.S. Geological Survey
    project geologist
    904 W. Riverside Ave
    Spokane, WA 99201-1087
    USA

    509-368-3106 (voice)
    509-368-3199 (FAX)
    sbox@usgs.gov

Why was the data set created?

This report presents the results of an assessment of Upper Paleozoic Chu-Sarysu sedimentary basin in central Kazakhstan for the occurrence of undiscovered sandstone copper deposits. The study was coordinated by the U.S. Geological Survey (USGS) as part of a cooperative international project to estimate the regional locations and probable quantity and quality of the world's undiscovered nonfuel mineral resources. This research project is developing, testing, and (or) applying a variety of methods to quantitatively assess undiscovered mineral resources to a depth of 1 km or more below the Earth's surface (Briskey and others, 2001, 2007; Schulz and Briskey, 2003). The primary objectives are to identify the principal areas in the world that have potential for selected undiscovered mineral resources using available compiled information about geology, geochemistry, geophysics, and previous exploration results in the context of modern quantitative statistical models. Regional assessment studies like this one compile and integrate existing information using GIS technology so that results can be presented at a scale of 1:1,000,000. Data sets include: databases and maps of the location, size, and geologic type of known mineral deposits and occurrences; maps and explanations of regional geology, metallogeny, tectonics, geochemistry, and geophysics; and available information about regional mineral exploration history. The integrated information is used to delineate tracts of land permissive for particular types of undiscovered nonfuel mineral deposits and to make and constrain probabilistic estimates of the quantity and quality of the undiscovered resources. The resulting quantitative mineral resource assessment then can be evaluated using economic filters and cash flow models for economic and policy analysis, and can be applied to mineral supply, economic, environmental, and land-use planning. Such economic evaluations are not part of this report. In this report, we first present an overview of the geologic setting and history of the Chu-Sarysu Basin. This is followed by a review of the characteristic features of sandstone copper deposits in general and of the giant Dzhezkazgan deposit in particular in order to develop a generalized model for the origin of these deposits in this basin. We then briefly review the mineral assessment methodology that has been developed by researchers at the U.S. Geological Survey. Finally, we summarize our mineral assessment of undiscovered sandstone copper deposits in the Chu-Sarysu Basin. Brief description is given of the data used in the assessment and of the criteria used to delineate the tracts that are permissive for the occurrence of undiscovered deposits of this type, and we compare the local deposits with the global grade-tonnage model to test its appropriateness. Finally, we review the results of the probabilistic assessments of the permissive tracts and the results of the Monte Carlo simulations of the contained metal endowment of each tract.

How was the data set created?

  1. From what previous works were the data drawn?

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

    (process 1 of 1)
    For details regarding steps taken as complex and disparate data sources were compiled and analyzed, please see this report:
    Box, S.E., Syusyura, B., Hayes, T.S., Taylor, C.D., Zientek, M.L., Hitzman, M.W., Seltmann, R., Chechetkin, V., Dolgopolova, A., Cossette, P.M., and Wallis, J.C., 2012, Sandstone copper assessment of the Chu-Sarysu Basin, central Kazakhstan: U.S. Geological Survey Scientific Investigations Report 2010-5090-E.

    Person who carried out this activity:

    Stephen E. Box
    U.S. Geological Survey
    project geologist
    904 W. Riverside Ave.
    Spokane, WA 99201-1087
    USA

    509-368-3199 (FAX)
    sbox@usgs.gov

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

    Syusyura, Boris, Box, Stephen E. , and Wallis, John C. , 2010, Spatial Databases of Geological, Geophysical, and Mineral Resource Data Relevant to Sandstone-Hosted Copper Deposits in Central Kazakhstan: Open-File Report Open-File Report 2010-1124, U.S. Geological Survey, Menlo Park, California.

    Online Links:

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

  1. How well have the observations been checked?

    Attribute accuracy was verified by manual comparison of the source maps with hard copy plots, printouts, and on-screen evaluation.

  2. How accurate are the geographic locations?

    The horizontal positional accuracy of the polygon features varies: it is dependent on several factors including the original scale of the base maps used in mapping the geology (which was subsequently used to delineate the mineral resource tracts).

  3. How accurate are the heights or depths?

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

    SIR2011-5090-E includes GIS spatial datasets (ESRI geodatabase feature classes) that describe four sediment-hosted copper tracts located in the Chu-Sarysu basin, Kazakhstan, Central Asia. These areas (tracts) were assessed by the USGS as part of the 2010 Global Minerals Resource Assessment Project and are the result of extensive analysis of data and assets acquired from and shared by CERCAMS and MEC.

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

    No duplicate features exist.

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:
This spatial database is not meant to be used or displayed at any scale larger than 1:1,000,000 (for example, 1:250,000). Any hardcopies utilizing these datasets shall clearly indicate their source. If the user has modified the data in any way, they are obligated to describe the types of modifications they have performed on the hardcopy map. User specifically agrees not to misrepresent these data sets, nor imply that changes they made were approved by the U.S. Geological Survey.

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

    U.S. Geological Survey Information Services
    P.O. Box 25286
    Denver, CO 80225
    USA

    (888) ASK-USGS (voice)
    infoservices@usgs.gov

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

    Downloadable data for USGS [Scientific Investigations Report, SIR] [2010-5090-E].

  3. What legal disclaimers am I supposed to read?

    The U.S. Geological Survey (USGS) provides these geographic data "as is." The USGS makes no guarantee or warranty concerning the accuracy of information contained in the geographic 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 these data have been processed successfully on computers of the USGS, no warranty, expressed or implied, is made by the USGS regarding the use of these data on any other system, nor does the fact of distribution constitute or imply such warranty. In no event shall the USGS have liability whatsoever for payment of any consequential, incidental, indirect, special, or tort damages of any kind, including, but not limited to, any loss of profits arising out of use of or reliance on the geographic data or arising out of the delivery, installation, operation, or support by the USGS. This spatial database is not meant to be used or displayed at any scale larger than 1:1,000,000 (for example, 1:250,000).

  4. How can I download or order the data?

  5. What hardware or software do I need in order to use the data set?

    User must have geographic information system (GIS) software capable of reading ESRI ArcGIS file formats

Who wrote the metadata?

Dates:
Last modified: 03-Oct-2012
Metadata author:
Pamela M. Cossette
U. S. Geological Survey
Geologist
904 W. Riverside Ave.
Spokane, WA 99201-1087
USA

509-368-3121 (voice)
509-368-3199 (FAX)
pcossette@usgs.gov

Generated by mp version 2.9.14 on Wed Oct 03 11:21:34 2012