David W. Anning

Digital spatial data for predicted nitrate and arsenic concentrations in basin-fill aquifers of the Southwest Principal Aquifers study area

This product “Digital spatial data for predicted nitrate and arsenic concentrations in basin-fill aquifers of the Southwest Principal Aquifers study area” is a 1:250,000-scale vector spatial dataset developed as part of a regional Southwest Principal Aquifers (SWPA) study (Anning and others, 2012). 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 localand basin-scale measures of source, aquifer susceptibility, and geochemical conditions. Background 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. Development of Classifiers 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. Supplemental Information 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 Anning and others (2012). The digital dataset can be downloaded from the USGS at http://water.usgs.gov/lookup/getspatial?ds2012-698_SWPA_ NO3_As_prediction. 2 Digital Spatial Data for Predicted Nitrate and Arsenic Concentrations in Basin-Fill Aquifers References Cited Anning, D.W., Paul, A.P., McKinney, T.S., Huntington, J.M., Bexfield, L.M., and Thiros, S.A., 2012, Predicted nitrate and arsenic concentrations in basin-fill aquifers of the southwestern United States: U.S. Geological Survey Scientific Investigations Report 2012–5065, 78 p. Available at http://pubs.usgs.gov/sir/2012/5065. M cKnney nd Aning— D iital Satial D ta or Pricted N irate nd A renic Contrations in B as-Fill A qifers of he Suthw st Prcipal A qifers Sudy A ra— Data Sries 98

Digital spatial data for observed, predicted, and misclassification errors for observations in the training dataset for nitrate and arsenic concentrations in basin-fill aquifers in the Southwest Principal Aquifers study area

This product “Digital spatial data for observed, predicted, and misclassification errors for observations in the training dataset for nitrate and arsenic concentrations in basin-fill aquifers in the Southwest Principal Aquifers study area” is a 1:250,000-scale point spatial dataset developed as part of a regional Southwest Principal Aquifers (SWPA) study (Anning and others, 2012). 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 localand basin-scale measures of source, aquifer susceptibility, and geochemical conditions. Background This dataset was developed as part of a regional Southwest Principal Aquifers (SWPA) study and for the National WaterQuality Assessment (NAWQA) Program. The dataset represents observed nitrate and arsenic concentrations that were used to train the confirmatory and prediction classifiers. Development of Classifiers 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. Supplemental Information The nitrate and arsenic observations, predictions, and misclassification error data for observations 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 site 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 Anning and others (2012). The digital dataset can be downloaded from the USGS at http://water.usgs.gov/lookup/ getspatial?ds2012-697_SWPA_NO3_As_training 2 Digital Spatial Data for Observed, Predicted, and Misclassification Errors

Hydrogeologic investigation of the Detrital, Hualapai, and Sacramento valleys of northwestern Arizona: a project of the Rural Watershed Initiative

U.S. Geological Survey Fact Sheet 2006–3008 March 2006 Printed on recycled paper The Detrital, Hualapai, and Sacramento Valleys are broad, intermountain desert basins in Mohave County, northwestern Arizona, and are home to residents in the city of Kingman and several rural communities (fig. 1). Ground water is the primary source of water in these valleys and is essential for many economic and cultural activities. As in many parts of the Western United States, population growth in these valleys is substantial. From 2000 to 2004, the population of Kingman grew from 20,100 to 24,600—an increase of 22 percent (Arizona Department of Economic Security, 2005). During the same time period, the population of Mohave County increased by 16 percent. Management of the available ground-water resources in these valleys guided by a comprehensive scientific understanding can help the growing communities to meet their needs in a sustainable manner. In 2005, the U.S. Geological Survey (USGS) began an investigation of the hydrogeology of the Detrital, Hualapai, and Sacramento Valleys in cooperation with the Arizona Department of Water Resources (ADWR) as part of the Rural Watershed Initiative (RWI), a program established by the State of Arizona and managed by the ADWR. Other projects in the RWI program include investigations that began in 2005 in the middle San Pedro Basin and the Willcox and Douglas Basins, and investigations that began in 1999 in the Coconino Plateau, the Mogollon Highlands, and upper and middle Verde River study areas (http://az.water.usgs.gov/rwi-ii/). Figure 1. Physiography and location of water-level and well-log data for Detrital, Hualapai, and Sacramento Valleys, northwestern Arizona. Kingman