Hitt, K.J. 2007 1 Raster digital data Reston, Virginia, USA U.S. Geological Survey http://water.usgs.gov/lookup/getspatial?gwava-dw_out 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 predicted nitrate concentration in ground water used for drinking, in milligrams per liter, in the conterminous United States, and was generated by a national nonlinear regression model based on 14 input parameters. 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 a national map of nitrate concentration (in milligrams per liter) in U.S ground water used for drinking as predicted by the GWAVA-DW model. The data set is one of 14 spatial data sets (1 output data set and 13 input data sets) associated with the GWAVA-DW model. Full details of the model development are in Nolan and Hitt (2006). This data set represents the model output, which is depicted in figure 3 of Nolan and Hitt (2006) that shows predicted nitrate concentration in milligrams per liter in ground water used for drinking. The model results can be used to indicate areas of the Nation that may be vulnerable to nitrate contamination. For inputs to the model, spatial attributes representing 13 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 ground water used for drinking (GWAVA-DW) > and corresponding input spatial data sets. > [kg, kilograms; km2, square kilometers.] > >Nitrogen Source Factors Data Set Name > 1 farm fertilizer (kg/hectare) gwava-dw_ffer > 2 confined manure (kg/hectare) gwava-dw_conf > 3 orchards/vineyards (percent) gwava-dw_orvi > 4 population density (people/km2) gwava-dw_popd > >Transport to Aquifer Factors > 5 water input (km2/cm) gwava-dw_wtin > 6 glacial till (yes/no) gwava-dw_gtil > 7 semiconsolidated sand aquifers gwava-dw_semc > (yes/no) > 8 sandstone and carbonate rocks gwava-dw_sscb > (yes/no) > 9 drainage ditch (km2) gwava-dw_ddit > 10 Hortonian overland flow gwava-dw_hor > (percent of streamflow) > >Attenuation Factors > 11 fresh surface water withdrawal gwava-dw_swus > for irrigation (megaliters/day) > 12 irrigation tailwater recovery (km2) gwava-dw_twre > 13 Dunne overland flow gwava-dw_dun > (percent of streamflow) > 14 well depth (meters) - "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. "Water input" is the ratio of the total area of irrigated land to precipitation, in square kilometers per centimeter. "Glacial till" is the presence or absence of poorly sorted glacial till east of the Rocky Mountains. "Semiconsolidated sand aquifers" is the presence or absence of semiconsolidated sand aquifers. "Sandstone and carbonate rocks" is the presence or absence of sandstone and carbonate rock aquifers. "Drainage ditch" is the area of National Resources Inventory surface drainage, field ditch conservation practice, in square kilometers. "Hortonian overland flow" is infiltration excess overland flow estimated by TOPMODEL, in percent of streamflow. "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. "Dunne overland flow" is saturation overland flow estimated by TOPMODEL, in percent of streamflow. "Well depth" is the depth of the well, in meters. Well depth was not compiled as a spatial data set. Well depth equals 50 meters for the model simulation being presented. 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 is the predicted nitrate concentration (mg/L) in U.S. ground water used for drinking and resulted from a nonlinear regression model based on 14 input parameters of nitrogen sources and transport and attenuation factors. 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-dw_orvi, gwava-dw_hor, gwava-dw_gtil, gwava-dw_semc, gwava-dw_sscb, gwava-dw_dun) 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. -128.30785909 -65.14338696 51.857984 22.73659812 None Ground water Ground water contamination Ground water pollution Ground water susceptibility Nutrients Nitrate National Water-Quality Assessment Program NAWQA Nonlinear model Nitrate concentration Drinking water inlandWaters None Conterminous United States None None None None None. The data set predicts nitrate concentration and does not necessarily indicate areas that actually are contaminated. The data is for national and regional use only, not for local applications. 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. http://water.usgs.gov/GIS/browse/gwava-dw_out.jpg Map of nitrate concentration in U.S. ground water used for drinking, as predicted by the GWAVA-DW model. JPG Thanks to Michael E. Wieczorek 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-dw_ffer Hitt, K.J. 2007 1 Raster digital data Reston, Virginia, USA U.S. Geological Survey http://water.usgs.gov/lookup/getspatial?gwava-dw_conf Hitt, K.J. 2007 1 Raster digital data Reston, Virginia, USA U.S. Geological Survey http://water.usgs.gov/lookup/getspatial?gwava-dw_orvi Hitt, K.J. 2007 1 Raster digital data Reston, Virginia, USA U.S. Geological Survey http://water.usgs.gov/lookup/getspatial?gwava-dw_popd Hitt, K.J. 2007 1 Raster digital data Reston, Virginia, USA U.S. Geological Survey http://water.usgs.gov/lookup/getspatial?gwava-dw_wtin Hitt, K.J. 2007 1 Raster digital data Reston, Virginia, USA U.S. Geological Survey http://water.usgs.gov/lookup/getspatial?gwava-dw_gtil Hitt, K.J. 2007 1 Raster digital data Reston, Virginia, USA U.S. Geological Survey http://water.usgs.gov/lookup/getspatial?gwava-dw_semc Hitt, K.J. 2007 1 Raster digital data Reston, Virginia, USA U.S. Geological Survey http://water.usgs.gov/lookup/getspatial?gwava-dw_sscb Hitt, K.J. 2007 1 Raster digital data Reston, Virginia, USA U.S. Geological Survey http://water.usgs.gov/lookup/getspatial?gwava-dw_ddit Hitt, K.J. 2007 1 Raster digital data Reston, Virginia, USA U.S. Geological Survey http://water.usgs.gov/lookup/getspatial?gwava-dw_hor Hitt, K.J. 2007 1 Raster digital data Reston, Virginia, USA U.S. Geological Survey http://water.usgs.gov/lookup/getspatial?gwava-dw_swus Hitt, K.J. 2007 1 Raster digital data Reston, Virginia, USA U.S. Geological Survey http://water.usgs.gov/lookup/getspatial?gwava-dw_twre Hitt, K.J. 2007 1 Raster digital data Reston, Virginia, USA U.S. Geological Survey http://water.usgs.gov/lookup/getspatial?gwava-dw_dun Hitt, K.J. 2007 1 Raster digital data Reston, Virginia, USA U.S. Geological Survey http://water.usgs.gov/lookup/getspatial?gwava-s_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." 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-DW, > units and estimated coefficients > [kg, kilograms; km2, square kilometers.] > >Nitrogen Loading Units Estimated coefficient > 1 farm fertilizer kg/hectare 0.1068 > 2 confined manure kg/hectare 0.1416 > 3 orchards/vineyards percent 0.2999 > 4 population density people/km2 0.0021 > >Transport Factors > 5 water input km2/cm 86.55 > 6 glacial till presence/absence -0.8658 > 7 semiconsolidated sand aquifers presence/absence 0.5057 > 8 sandstone and carbonate rocks presence/absence 0.3641 > 9 drainage ditch km2 -5.080 > 10 Hortonian overland flow percent of streamflow -0.0330 > >Attenuation Factors > 11 fresh surface water withdrawal megaliters/day -1.334 > 12 irrigation tailwater recovery km2 -13.84 > 13 Dunne overland flow percent of streamflow -0.1443 > 14 well depth meters -0.00163 More information on sources of these data layers and GIS procedures used to develop the data sets are given in the descriptions of the 14 individual input spatial data sets. (See Identification_Information, Cross_Reference listings). 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 input data for Hortonian overland flow contained large areas of "no data" in Arizona, Utah, and Idaho, which resulted in the same areas being coded as "no data" in output cells. The following ArcInfo Workstation GRID commands produced the predicted nitrate concentration grid: >/*Nonlinear regression model 2 for nitrate in drinking water wells. Depth 50 meters. >/*Fertilizer and manure units are kg/ha (usegha) >/*Feb 01 2006 >/*Remove filter on fertilizer, manure, population. Revise filter on precip to be 99x99 rectangle, >/* instead of 9x9 kernel. >setwindow -2380000.000 260000.000 2265000.000 3200000.000 gwava-dw_orvi >setcell 1000 >/*Set directory housing the filtered input grid for precip. >&s fdir = d:/ancill/model2005/dec2005/filtered >/* >gwava-dw_out = ((0.106751 * gwava-dw_ffer) + (0.141597 * gwava-dw_conf) + (0.299863 * gwava-dw_orvi) + (0.0021 * gwava-dw_popd)) * ~ >exp ((-5.08005 * gwava-dw_ddit) + (-0.03299 * gwava-dw_hor) + (-0.86585 * gwava-dw_gtil) + (0.505704 * gwava-dw_semc) + (0.364065 * gwava-dw_sscb) + ~ > (86.54621 * %fdir%/gwava-dw_wtin)) * ~ >exp ((-1.33354 * gwava-dw_swus) + (-13.8388 * gwava-dw_twre) + (-0.14432 * gwava-dw_dun) + (-0.00163 * 50)) 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 GRID was converted to ASCII (plain text) for distribution using ArcInfo Workstation command: >gridascii gwava-dw_out gwava-dw_out.txt 2007 Raster Grid Cell 2940 4645 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 the nitrate concentration in units of milligrams per liter (mg/L) predicted by the GWAVA-DW model. Data Type: Floating Point Minimum Value = 0.000 Maximum Value = 1164.637 Mean = 0.939 Standard Deviation = 4.329 The grid is floating point; a VAT is not present. 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-dw_out 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 17065306 bytes http://water.usgs.gov/GIS/dsdl/gwava-dw/arctar/gwava-dw_out.tgz ASCII file gzip -d; gunzip 22280637 bytes http://water.usgs.gov/GIS/dsdl/gwava-dw/gascii/gwava-dw_out.txt.gz Index to all files related to the GWAVA-DW 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-dw/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