Tim S. McKinney 2012 vector digital data Reston, VA U.S. Geological Survey http://water.usgs.gov/lookup/getspatial?ds2012-698_SWPA_NO3_As_prediction David W. Anning Angela P. Paul Tim S. McKinney Jena M. Huntington Laura M. Bexfield Susan A. Thiros 2012 U.S. Geological Survey Scientific Investigations Report SIR-2012-5065 Tucson, AZ U.S. Geological Survey http://pubs.usgs.gov/ds/697/ This product "Predicted nitrate and arsenic concentrations in basin-fill aquifers of the Southwest Principal Aquifers study area" is a 1:250,000-scale vector dataset and was developed as part of a regional Southwest Principal Aquifers (SWPA) study. The study examined the vulnerability of basin-fill aquifers in the southwestern United States to nitrate contamination and arsenic enrichment. Statistical models were developed by using the random forest classifier algorithm to predict concentrations of nitrate and arsenic across a model grid that represents local- and basin-scale measures of source, aquifer susceptibility, and geochemical conditions. Separate classifiers were developed for nitrate and arsenic because each constituent was expected to be affected by a different set of factors, and each factor could have a different magnitude or directional influence (increase/decrease) on concentration. For each constituent, two different classifiers were developed; a prediction classifier and a confirmatory classifier. The prediction classifiers were developed specifically to predict nitrate and arsenic concentrations in basin-fill aquifers across the SWPA study area and were based on explanatory variables representing source and susceptibility conditions. These explanatory variables were available throughout the entire SWPA study area and, therefore, did not pose a limitation for using the classifiers to predict concentrations. The confirmatory classifiers were developed to supplement the prediction classifiers in the evaluation of the conceptual model. The name, "confirmatory," reflects the classifier's purpose for evaluation of a-priori hypotheses and contrasts other general types of statistical models, such as those used for prediction or exploratory purposes. The confirmatory classifiers included the explanatory variables used in the prediction classifiers, as well as additional variables representing geochemical conditions and basin groundwater budget components. The inclusion of the geochemical and basin groundwater budget variables in the confirmatory classifiers allowed for further evaluation of the conceptual models, which was not possible with the prediction classifiers alone. The geochemical data, however, were only available at specific well locations, and consistent water-budget data were not available for every basin in the study area. The limited availability of the data for these variables constrained the confirmatory classifiers to observations from 16 case-study basins and precluded use of the confirmatory classifier for predicting concentrations across the SWPA study area. To contrast the scope of the two classifiers, the confirmatory classifiers were developed by using all available explanatory variables but with observations restricted to the 16 case-study basins, whereas the prediction classifiers were unrestricted with respect to spatial extent because these were developed by using a subset of the explanatory variables that were available throughout the study area. This dataset was developed as part of a regional Southwest Principal Aquifers (SWPA) study and for the National Water-Quality Assessment (NAWQA) Program. The dataset represents the spatial and statistical distribution of nitrate and arsenic concentrations that were determined from the prediction classifiers for basin-fill aquifers across the SWPA study area. The nitrate and arsenic predictions are part of a larger dataset of explanatory variables and model input data. Those data are archived in tabular form along with the model report. The explanatory data may be joined to this dataset via the grid cell identifier. For more information on the development of the explanatory variables, see "Compilation and Processing of Explanatory Variables" in the "Approach and Methods" section of SIR-2012-5065. 1980 2009 2012 ground condition Complete None planned -124.889549 -104.566268 44.627454 29.300033 ISO 19115 Topic Category geoscientificInformation inlandWaters environment utilitiesCommunication None Water quality Nitrate concentration Arsenic concentration Basin-fill aquifer Groundwater Groundwater contamination Groundwater susceptibility National Water-Quality Assessment Program NAWQA None Southwest United States California Utah Colorado New Mexico Arizona Nevada None These data are not intended to be used as a survey product and are for reference purposes only. Southwestern US only. Although this Federal Geographic Data Committee (FGDC) compliant metadata file is intended to document the data set in nonproprietary form, as well as ArcGIS format, this metadata file may include some ArcGIS-specific terminology. Acknowledgment of the U.S. Geological Survey would be appreciated in products derived from these data. U.S. Geological Survey, Arizona Water Center Director mailing and physical address

520 N. Park Avenue, Suite 221

Tucson Arizona 85719-5035 USA (520) 670-6671 (520) 670-5592 7:30 a.m. to 4:00 p.m. Mountain Time http://water.usgs.gov/GIS/browse/ds2012-697_SWPA_NO3_As_prediction.jpg Illlustration of data set jpg Microsoft Windows XP Version 5.1 (Build 2600) Service Pack 3; ESRI ArcCatalog 9.3.1.4000 Tim S. McKinney 2008 raster digital data Reston, Virginia U.S. Geological Survey http://water.usgs.gov/lookup/getspatial?sir2008-5239_swpa_agir_wu_2000 Tim S. McKinney 2008 vector digital data http://water.usgs.gov/lookup/getspatial?sir2008-5239_swpa_basin_stats Tim S. McKinney 2008 raster digital data http://water.usgs.gov/lookup/getspatial?sir2008-5239_swpa_geo Tim S. McKinney 2008 raster digital data http://water.usgs.gov/lookup/getspatial?sir2008-5239_swpa_hga Tim S. McKinney 2008 raster digital data http://water.usgs.gov/lookup/getspatial?sir2008-5239_swpa_public_supply_wu_2005 Tim S. McKinney 2012 vector digital data http://water.usgs.gov/lookup/getspatial?ds697_SWPA_NO3_As_training Training observations classifications summary for the prediction random forest classifiers of nitrate and arsenic concentrations in basin-fill aquifers of the Southwest Principal Aquifers study area. Nitrate predictions: Percent of observations classified in correct class, 42.3% Percent of observations classified in correct class, one class above, or one class below, 72.5 Arsenic predictions: Percent of observations classified in correct class, 34.4% Percent of observations classified in correct class, one class above, or one class below, 70.2% For more information see the Nitrate and Arsenic Classifiers and Predicted Concentrations section and tables 7 and 13 of SIR-2012-5065. Tests of valid values were spot checked with input datasets. No inconsistencies were observed Complete for the basin-fill aquifers of the Southwest U.S. Not for use at scales greater than 1:250,000. None David W. Anning 2012 Reston, VIriginia U.S. Geological Survey For a complete list of model input data and sources, please see SIR-2012-5065 and: Appendix 2_PedictionSet.xlsx, Appendix 1_TrainingSet.xlsx, and Table 3_List of explanatory variables.xlsx Anning and Others, 2012 2012 U.S. Geological Survey Scientific Investigations Report SIR-2012-5065 Tucson, AZ U.S. Geological Survey online 1980 2009 2012 ground condition PredictionSet Provided nitrate and arsenic prediction values for 3-kilometer grid cells. Tim S. McKinney Unpublished Material vector digital data 2009 2009 g3k Vector 3-kilometer grid of model cells. Joined model prediction output data to vector model grid PredictionSet g3k 20100826 swpa_N03_As_predictions Vector G-polygon 54854 Albers Conical Equal Area 29.500000 45.500000 -96.000000 23.000000 0.000000 0.000000 coordinate pair 1.000000 1.000000 meters North American Datum of 1983 Geodetic Reference System 80 6378137.000000 298.257222 ds2012-698_swpa_NO3_As_prediction.shp Polygon feature class ESRI FID Internal feature number. ESRI Sequential unique whole numbers that are automatically generated. Shape Feature geometry. ESRI Coordinates defining the features. cell_id Grid cell identifier USGS Unique value used to identify a model grid cell cell_lon Longitude of well in decimal degrees, NAD83. USGS -124.353951 -105.240558 decimal degrees cell_lat Latitude of well in decimal degrees, NAD83. USGS 31.322835 42.566044 decimal degrees bsn_id Alluvial basin identifier USGS Unique value used to identify an alluvial basin bsn_name Alluvial basin name USGS Hydrogeologic Areas of the Southwest Principal Aquifer (SWPA) study USGS aq_name Principal aquifer name USGS U.S. Geological Survey National Atlas USGS state US State State State name State NO3_cls Predicted nitrate class, aquifer penetration depth of 200 ft. USGS 1 <0.50 mg/L USGS 2 0.50-0.99 mg/L USGS 3 1.0-1.9 mg/L USGS 4 2.0-4.9 mg/L USGS 5 5.0-9.9 mg/L USGS 6 >=10 mg/L USGS -999999 NoData USGS NO3_mgL Predicted nitrate concentration, aquifer penetration depth of 200 ft. USGS <0.50 >=10 milligrams per liter NO3_chg_wd Change in predicted nitrate concentration with aquifer penetration depths 50 to 1000 ft. USGS No Change No change in predicted nitrate concentration with change in depth USGS Decrease Decreasing nitrate concentration with change in depth USGS Increase Increasing nitrate concentration with change in depth USGS as_cls Predicted arsenic class, aquifer penetration depth of 200 ft. USGS 1 <1.0 ug/L USGS 2 1.0-1.9 ug/L USGS 3 2.0-2.9 ug/L USGS 4 3.0-4.9 ug/L USGS 5 5.0-9.9 ug/L USGS 6 10-24 ug/L USGS 7 >=25 ug/L USGS -999999 NoData USGS as_ugL Predicted arsenic concentration, aquifer penetratoni depth of 200 ft. USGS <1.0 >=25 micrograms per liter as_chg_wd Change in predicted arsenic concentration with aquifer penetration depths 50 to 1000 USGS No Change No Change in arsenic concentration with change in depth USGS Decrease Decreasing arsenic concentration with change in depth USGS Increase Increasing arsenic concentration with change in depth USGS U.S. Geological Survey Ask USGS -- Water Webserver Team mailing address

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Reston VA 20192 USA 1-888-275-8747 (1-888-ASK-USGS) http://water.usgs.gov/user_feedback_form.html Downloadable Data Although these data have 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. 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 these data, software, or related materials. The use of firm, trade, or brand names in this report is for identification purposes only and does not constitute endorsement by the U.S. Geological Survey. The names mentioned in this document may be trademarks or registered trademarks of their respective trademark owners. ESRI Shapefile Spatial and attribute information Winzip 1000 http://water.usgs.gov/GIS/dsdl/ds2012-698_SWPA_NO3_As_prediction.zip None. This dataset is provided by USGS as a public service. 20120201 U.S. Geological Survey REQUIRED: The person responsible for the metadata information. Ask USGS -- Water Webserver Team mailing address

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Reston VA 20192 USA 1-888-275-8747 (1-888-ASK-USGS) http://answers.usgs.gov/cgi-bin/gsanswers?pemail=h2oteam&subject=GIS+Dataset+ds698_SWPA_NO3_As_prediction FGDC Content Standards for Digital Geospatial Metadata FGDC-STD-001-1998 local time