Hitt, K.J. 2007 1 Raster digital data Reston, Virginia, USA U.S. Geological Survey http://water.usgs.gov/lookup/getspatial?gwava-s_hist Nolan, B.T. Hitt, K.J. 2006 Environmental Science and Technology Volume 40, Number 24, pages 7834-7840 http://water.usgs.gov/nawqa/nutrients/pubs/est_v40_no24/ http://pubs3.acs.org/acs/journals/doilookup?in_doi=10.1021/es060911u This data set represents the amount of histosols soil taxonomic order, in percent, in the conterminous United States. The data set was used as an input data layer for a national model to predict nitrate concentration in shallow ground water. Nolan and Hitt (2006) developed two national models to predict contamination of ground water by nonpoint sources of nitrate. The nonlinear approach to national-scale Ground-WAter Vulnerability Assessment (GWAVA) uses components representing nitrogen (N) sources, transport, and attenuation. One model (GWAVA-S) predicts nitrate contamination of shallow (typically less than 5 meters deep), recently recharged ground water, which may or may not be used for drinking. The other (GWAVA-DW) predicts ambient nitrate concentration in deeper supplies used for drinking. This data set is one of 17 data sets (1 output data set and 16 input data sets) associated with the GWAVA-S model. Full details of the model development are in Nolan and Hitt (2006). For inputs to the model, spatial attributes representing 16 nitrogen loading and transport and attenuation factors were compiled as raster data sets (1-km by 1-km grid cell size) for the conterminous United States (see table 1). >Table 1.-- Parameters of nonlinear regression model for nitrate in shallow > ground water (GWAVA-S) and corresponding input spatial data sets. > [kg, kilograms; km2, square kilometers.] > >Nitrogen Source Factors Data Set Name > 1 farm fertilizer (kg/hectare) gwava-s_ffer > 2 confined manure (kg/hectare) gwava-s_conf > 3 orchards/vineyards (percent) gwava-s_orvi > 4 population density (people/km2) gwava-s_popd > 5 cropland/pasture/fallow (percent) gwava-s_crpa > >Transport to Aquifer Factors > 6 water input (km2/cm) gwava-s_wtin > 7 carbonate rocks (yes/no) gwava-s_crox > 8 basalt and volcanic rocks (yes/no) gwava-s_vrox > 9 drainage ditch (km2) gwava-s_ddit > 10 slope (percent x 1000) gwava-s_slop > 11 glacial till (yes/no) gwava-s_gtil > 12 clay sediment (percent x 1000) gwava-s_clay > >Attenuation Factors > 13 fresh surface water withdrawal gwava-s_swus > for irrigation (megaliters/day) > 14 irrigation tailwater recovery (km2) gwava-s_twre > 15 histosol soil type (percent) gwava-s_hist > 16 wetlands (percent) gwava-s_wetl "Farm fertilizer" is the average annual nitrogen input from commercial fertilizer applied to agricultural lands, 1992-2001, in kilograms per hectare. "Confined manure" is the average annual nitrogen input from confined animal manure, 1992 and 1997, in kilograms per hectare. "Orchards/vineyards" is the percent of orchards/vineyards land cover classification. "Population density" is 1990 block group population density, in people per square kilometer. "Cropland/pasture/fallow" is the percent of cropland/pasture/fallow land cover classifications. "Water input" is the ratio of the total area of irrigated land to precipitation, in square kilometers per centimeter. "Carbonate rocks" is the presence or absence of Valley and Ridge carbonate rocks. "Basalt and volcanic rocks" is the presence or absence of basalt and volcanic rocks. "Drainage ditch" is the area of National Resources Inventory surface drainage, field ditch conservation practice, in square kilometers. "Slope" is the soil surface slope, in percent times 1000. "Glacial till" is the presence or absence of poorly sorted glacial till east of the Rocky Mountains. "Clay sediment" is the amount of clay sediment in the soil, in percent times 1000. "Fresh surface water withdrawal for irrigation" is the amount of fresh surface water withdrawal for irrigation, in megaliters per day. "Irrigation tailwater recovery" is the area of National Resources Inventory irrigation system, tailwater recovery conservation practice, in square kilometers. "Histosol soil type" is the amount of histosols soil taxonomic order, in percent. "Wetlands" is the percent of woody wetlands and emergent herbaceous wetlands land cover classifications. Reference cited: Nolan, B.T. and Hitt, K.J., 2006, Vulnerability of shallow ground water and drinking-water wells to nitrate in the United States: Environmental Science and Technology, vol. 40, no. 24, pages 7834-7840. This particular data layer was created to help characterize nitrogen attenuation factors at a national level for input to a national model to predict nitrate concentration in shallow ground water. Nitrate is considered to be the most widespread contaminant in ground water. High nitrate concentration in ground water is a concern for human health, and protecting drinking water sources is a national priority. The U.S. Geological Survey's National Water-Quality Assessment (NAWQA) Program monitors the occurrence and distribution of nitrate and other contaminants in ground water and streams. However, because monitoring everywhere for the occurrence and distribution of nitrate in ground water is impractical, national water-quality models are used to address data gaps. The goal of the current study was to predict ground water vulnerability to nitrate at the national scale, to complement measured data. The data set is provided as native ESRI ArcInfo Workstation GRID and as ASCII text (plain text) format. The file "gridname".tgz file contains the GRID in a directory (folder) called arctar00000, where "gridname" is the name of the data set. For example, a GRID without a VAT (value attribute table) has the following files: >arctar00000/ >arctar00000/gridname/ >arctar00000/gridname/dblbnd.adf >arctar00000/gridname/hdr.adf >arctar00000/gridname/log >arctar00000/gridname/metadata.xml >arctar00000/gridname/prj.adf >arctar00000/gridname/sta.adf >arctar00000/gridname/w001001.adf >arctar00000/gridname/w001001x.adf >arctar00000/info/ >arctar00000/info/arc.dir >arctar00000/info/arc0000.dat >arctar00000/info/arc0000.nit >arctar00000/info/arc0001.dat >arctar00000/info/arc0001.nit >arctar00000/log A GRID with a VAT (value attribute table) (gwava-s_orvi, gwava-s_crpa, gwava-s_crox, gwava-s_vrox, gwava-s_slop, gwava-s_gtil, gwava-s_clay, gwava-s_hist, gwava-s_wetl) has these files: >arctar00000/ >arctar00000/gridname/ >arctar00000/gridname/dblbnd.adf >arctar00000/gridname/hdr.adf >arctar00000/gridname/log >arctar00000/gridname/metadata.xml >arctar00000/gridname/prj.adf >arctar00000/gridname/sta.adf >arctar00000/gridname/vat.adf >arctar00000/gridname/w001001.adf >arctar00000/gridname/w001001x.adf >arctar00000/gridname.aux >arctar00000/info/ >arctar00000/info/arc.dir >arctar00000/info/arc0000.dat >arctar00000/info/arc0000.nit >arctar00000/info/arc0001.dat >arctar00000/info/arc0001.nit >arctar00000/info/arc0002.dat >arctar00000/info/arc0002.nit >arctar00000/info/arc0002r.001 >arctar00000/log To extract the ArcInfo Workstation GRID from the "gridname".tgz archive file, use TARARC, WINZIP, or the following commands: >gunzip gridname.tgz >tar xvof gridname.tar The data set is provided in ASCII text format in addition to the native ESRI ArcInfo Workstation GRID format in case the user's software cannot access the data in ArcInfo Workstation GRID format. The ASCII file is compressed using gzip as "gridname".txt.gz, where "gridname" is the data set name. 1991 2003 Water-quality data used in this study were collected during 1991-2003 and represent the first full decade of sampling by the NAWQA program. The input data layers describe conditions in the mid 1990's, and so the predictions represent mid 1990's land-use and nitrogen-loading conditions. Complete None planned. -127.97736605 -65.11883061 51.691800 23.09338233 None Ground water Ground water contamination Ground water pollution Ground water susceptibility Nutrients Nitrate National Water-Quality Assessment Program NAWQA Nonlinear model Nitrate concentration inlandWaters Histosols None Conterminous United States None None None None None. This spatial data set is one of a group of data sets developed specifically for use in a national model of nitrate in ground water. The data set should be used at the national or regional level, not at the local level. Users should consider the various assumptions that went into generating each spatial data set and the limitations inherent in the source data materials in deciding whether the data set is appropriate for use in other national or regional applications. Please acknowledge the U.S. Geological Survey in products derived from these data. Thanks to Nancy T. Baker who reviewed the metadata and provided useful comments. Microsoft Windows XP Version 5.1 (Build 2600) Service Pack 2; ESRI ArcCatalog 9.0.0.535 Nolan, B.T. 2001 1 Ground Water Volume 39, Number 2, pages 290-299 http://water.usgs.gov/nawqa/nutrients/pubs/gw_v39_no2/ Nolan, B.T., Hitt, K.J., and Ruddy, B.C. 2002 1 Raster digital data Environmental Science & Technology Volume 36, Number 10, pages 2138-2145 http://water.usgs.gov/nawqa/nutrients/pubs/est_v36_no10/ http://water.usgs.gov/lookup/getspatial?gwrisk Nolan, B.T. Hitt, K.J. 2006 Environmental Science and Technology Volume 40, Number 24, pages 7834-7840 Denver, Colorado U.S. Geological Survey http://water.usgs.gov/nawqa/nutrients/pubs/est_v40_no24/ http://pubs3.acs.org/acs/journals/doilookup?in_doi=10.1021/es060911u Hitt, K.J. 2007 1 Raster digital data Reston, Virginia, USA U.S. Geological Survey http://water.usgs.gov/lookup/getspatial?gwava-s_out Hitt, K.J. 2007 1 Raster digital data Reston, Virginia, USA U.S. Geological Survey http://water.usgs.gov/lookup/getspatial?gwava-s_ffer Hitt, K.J. 2007 1 Raster digital data Reston, Virginia, USA U.S. Geological Survey http://water.usgs.gov/lookup/getspatial?gwava-s_conf Hitt, K.J. 2007 1 Raster digital data Reston, Virginia, USA U.S. Geological Survey http://water.usgs.gov/lookup/getspatial?gwava-s_orvi Hitt, K.J. 2007 1 Raster digital data Reston, Virginia, USA U.S. Geological Survey http://water.usgs.gov/lookup/getspatial?gwava-s_popd Hitt, K.J. 2007 1 Raster digital data Reston, Virginia, USA U.S. Geological Survey http://water.usgs.gov/lookup/getspatial?gwava-s_crpa Hitt, K.J. 2007 1 Raster digital data Reston, Virginia, USA U.S. Geological Survey http://water.usgs.gov/lookup/getspatial?gwava-s_wtin Hitt, K.J. 2007 1 Raster digital data Reston, Virginia, USA U.S. Geological Survey http://water.usgs.gov/lookup/getspatial?gwava-s_crox Hitt, K.J. 2007 1 Raster digital data Reston, Virginia, USA U.S. Geological Survey http://water.usgs.gov/lookup/getspatial?gwava-s_vrox Hitt, K.J. 2007 1 Raster digital data Reston, Virginia, USA U.S. Geological Survey http://water.usgs.gov/lookup/getspatial?gwava-s_ddit Hitt, K.J. 2007 1 Raster digital data Reston, Virginia, USA U.S. Geological Survey http://water.usgs.gov/lookup/getspatial?gwava-s_slop Hitt, K.J. 2007 1 Raster digital data Reston, Virginia, USA U.S. Geological Survey http://water.usgs.gov/lookup/getspatial?gwava-s_gtil Hitt, K.J. 2007 1 Raster digital data Reston, Virginia, USA U.S. Geological Survey http://water.usgs.gov/lookup/getspatial?gwava-s_clay Hitt, K.J. 2007 1 Raster digital data Reston, Virginia, USA U.S. Geological Survey http://water.usgs.gov/lookup/getspatial?gwava-s_swus Hitt, K.J. 2007 1 Raster digital data Reston, Virginia, USA U.S. Geological Survey http://water.usgs.gov/lookup/getspatial?gwava-s_twre Hitt, K.J. 2007 1 Raster digital data Reston, Virginia, USA U.S. Geological Survey http://water.usgs.gov/lookup/getspatial?gwava-s_wetl Hitt, K.J. 2007 1 Raster digital data Reston, Virginia, USA U.S. Geological Survey http://water.usgs.gov/lookup/getspatial?gwava-dw_out The model results were checked using standard USGS review procedures. Not applicable for raster data. The data spans the conterminous United States. An output cell was assigned a value of "no data" if any of the corresponding input data cells at that location was "no data." Wolock, D.M. 1997 raster digital data USGS Open-File Report 656 Lawrence, KS U.S. Geological Survey http://water.usgs.gov/lookup/getspatial?muid On-line 1994 Publication date of STATSGO data MUID STATSGO (State Soil Geographic) data is the source for percent histosols. Wolock (1997) gridded the STATSGO soil mapping units at 1-km resolution for the conterminous United States. Each soil mapping unit is identified by a unique code called MUID. Separate files (MUID.COMP, MUID.LAYER and others), also keyed by MUID, list weighted average values for selected STATSGO soil characteristics. Wolock computed the weighted average values by aggregating all of the soil layers and components comprising each mapping unit. [Retrieved March 2000.] Wolock's methods were used to calculate percent histosols. Spatial data sets representing nitrogen (N) loading and transport and attenuation factors were compiled for the conterminous United States. N source variables include farm fertilizer, manure from confined animal feeding operations, and loading surrogates that reflect additional sources of N. For example, population density is a surrogate for nonagricultural sources of N from septic tanks, sewers, and domestic animal waste in urban areas. Transport factors include water input, sediments, rock type, and selected management practices. "Water input" is an interaction term expressed as the ratio of the total area of irrigated land to precipitation. Attenuation factors include variables that are surrogates for dilution and/or denitrification. Each of the variables in the model was compiled within 1-km by 1-km grid cells for prediction of nitrate concentration at the national scale. >Table 2.-- Variables compiled for regression model GWAVA-S, > units and estimated coefficients > [kg, kilograms; km2, square kilometers.] > >Nitrogen Loading Units Estimated coefficient > 1 farm fertilizer kg/hectare 0.2265 > 2 confined manure kg/hectare 0.4049 > 3 orchards/vineyards percent 1.9600 > 4 population density people/km2 0.006658 > 5 cropland/pasture/fallow percent 0.1473 > >Transport Factors > 6 water input km2/cm 38.16 > 7 carbonate rocks presence/absence 0.5630 > 8 basalt and volcanic rocks presence/absence 0.5182 > 9 drainage ditch km2 -6.483 > 10 slope percent* -0.03861 > 11 glacial till presence/absence -0.8141 > 12 clay sediment percent* -0.04751 > >Attenuation Factors > 13 fresh surface water withdrawal megaliters/day -1.078 > 14 irrigation tailwater recovery km2 -8.327 > 15 histosol soil type percent -0.0185 > 16 wetlands percent -0.03213 > >*Values in the SLOPE and CLAY grids were multiplied by 1000 to convert > the grids from floating point to integer. 200512 Soil characteristics for HISTOSOLS were computed using Wolock's (1997) method for computing weighted averages for soil characteristics obtained from STATSGO tables (D. Wolock, written commun., 2000). The soil taxonomic orders were obtained from the STATSGO TAXCLASS table and are: >A Alfisols >C Andisols >D Aridisols >E Entisols >H Histosols >I Inceptisols >M Mollisols >O Oxisols >S Spodosols >U Ultisols >V Vertisols Up to three soil orders and the percentage of each were compiled for each mapping unit (D. Wolock, written commun., 2000). >ORDER1 = first soil order comprising part of the mapping unit >ORDER2 = second soil order comprising part of the mapping unit >ORDER3 = third soil order comprising part of the mapping unit >PRCTN1ORD = percent of ORDER1 in the mapping unit >PRCNT2ORD = percent of ORDER2 in the mapping unit >PRCNT3ORD = percent of ORDER3 in the mapping unit >COMPPERORD = percentage of all components of a soil mapping > unit covered by ORDER1, ORDER2, ORDER3 If Histosols soil order was present in ORDER1, ORDER2, or ORDER3, the corresponding percent of the mapping unit was used to indicate percent Histosols. For example, the four mapping units listed below show the three soil orders present in each. Histosols may or may not be shown in ORDER1, ORDER2, or ORDER3. >MUID ORDER1 PRCNT1ORD ORDER2 PRCNT2ORD ORDER3 PRCNT3ORD >AL005 I 64.0 U 22.0 M 10.0 >AL191 U 88.0 E 9.0 H 3.0 >AL194 E 43.0 H 23.0 U 18.0 >AL222 H 53.0 E 23.0 I 12.0 Extracting percent Histosols gives the following for each mapping unit: >MUID PERCENT HISTOSOLS >AL005 0 >AL191 3 >AL194 23 >AL222 53 The values of HISTOSOLS (percent) were put into a national grid of soil mapping units by relating on MUID. 200512 To make the national map of predicted nitrate concentration, the values from the 1-km by 1-km grid cells for each of the input data layers were put in to the model equation to calculate a predicted concentration for each output cell. An output cell was assigned a value of "no data" if any of the corresponding input data cells at that location was "no data." The following ArcInfo Workstation GRID commands produced the predicted nitrate concentration grid: >/*Nonlinear regression model 1 for nitrate in shallow ground water >/*Dec 23, 2005 >setwindow -2380000.000 260000.000 2265000.000 3200000.000 gwava-s_orvi >setcell 1000 >/*Set directory housing the filtered input grids for fertilizer, manure, population, and water input. >&s fdir = d:/ancill/model2005/dec2005/filtered >/* >/*Use filtered N input grids in kg/hectare. >/* >gwava-s_out = ((0.226544 * %fdir%/gwava-s_ffer) + (0.404948 * %fdir%/gwava-s_conf) + (1.959994 * gwava-s_orvi) + (0.006658 * gwava-s_popd) + ~ >(0.147298 * gwava-s_crpa)) * ~ >exp ((0.562985 * gwava-s_crox) + (0.518172 * gwava-s_vrox) + (-6.48311 * gwava-s_ddit) + (-0.03861 * ((gwava-s_slop / 1000))) + ~ >(-0.81412 * gwava-s_gtil) + (-0.04751 * (gwava-s_clay / 1000)) + (38.16395 * %fdir%/gwava-s_wtin)) * ~ >exp ((-1.07756 * gwava-s_swus) + (-8.3267 * gwava-s_twre) + (-0.01846 * gwava-s_hist) + (-0.03213 * gwava-s_wetl)) GRID cells were randomly selected from this data set and were checked by hand to ensure the correct values were calculated using the model equation and the input data layers. Areas with high N load, low to moderate clay content, sufficient water input, and low denitrification potential have the highest predicted nitrate concentration in ground water and therefore may be vulnerable to nitrate contamination. The most extensive areas of predicted, severe contamination (nitrate greater than 10 mg/L) occur in the High Plains, and areas of predicted, moderate contamination (more than 5 to 10 mg/L nitrate) occur extensively in the northern Midwest. 200512 The input GRID was converted to ASCII (plain text) for distribution using ArcInfo Workstation command: >gridascii gwava-s_hist gwava-s_hist.txt 2007 Raster Grid Cell 2887 4633 1 Albers Conical Equal Area 29.5 45.5 -96 23 0.00000 0.00000 row and column 1000.0 1000.0 METERS North American Datum of 1983 GRS80 6378137.000000 294.257222 Each 1-km by 1-km grid cell stores histosols in units of percent. Data Type: Integer Number of Values = 84 Minimum Value = 0.000 Maximum Value = 100.000 Mean = 1.316 Standard Deviation = 8.080 A VAT is present. VALUE is percent, and COUNT is the number of cells of each VALUE. In the ASCII text file, "no data" is indicated as -9999. None. U.S. Geological Survey Ask USGS -- Water Webserver Team mailing

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Reston VA 20192 1-888-275-8747 (1-888-ASK-USGS) http://answers.usgs.gov/cgi-bin/gsanswers?pemail=h2oteam&subject=GIS+Dataset+gwava-s_hist Although this data set has been used by the U.S. Geological Survey, U.S. Department of the Interior, no warranty expressed or implied is made by the U.S. Geological Survey as to the accuracy of the data and related materials. The act of distribution shall not constitute any such warranty, and no responsibility is assumed by the U.S. Geological Survey in the use of this data, software, or related materials. Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government. ArcInfo Workstation GRID gzip -d; gunzip 353685 bytes http://water.usgs.gov/GIS/dsdl/gwava-s/arctar/gwava-s_hist.tgz ASCII file gzip -d; gunzip 410156 bytes http://water.usgs.gov/GIS/dsdl/gwava-s/gascii/gwava-s_hist.txt.gz Index to all files related to the GWAVA-S model to facilitate downloading all the GIS data sets Web page with links to all data sets HTML 5 bytes http://water.usgs.gov/GIS/dsdl/gwava-s/index.html None. This data set is provided by USGS as a public service. 200704 U.S. Geological Survey Ask USGS -- Water Webserver Team mailing

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Reston VA 20192 1-888-275-8747 (1-888-ASK-USGS) http://water.usgs.gov/user_feedback_form.html FGDC Content Standards for Digital Geospatial Metadata FGDC-STD-001-1998