Documented in this data release are data used to model and map the probability of arsenic being greater than 10 micrograms per liter in private domestic wells throughout the conterminous United States during drought conditions (Lombard and others, 2020). The model used to predict the probability of arsenic exceeding 10 micrograms per liter in private domestic wells was previously developed and documented by Ayotte and others (2017). Independent variables in the model include groundwater recharge and annual precipitation. In order to assess the impact of drought these variables were altered to simulate drought by reducing the 30-year average annual values by 25 and 50 percent. The impact of drought was also assessed by using groundwater recharge and precipitation values from the year 2012 when approximately 66 percent of the contiguous United States experienced drought. Data sources for groundwater recharge and precipitation for the year 2012 differ from those used in the original model and the drought simulations, therefore a 30-year average climate model was also produced using these new data sources (Thornton and others, 2018; Hay, 2019). Data are documented from the original model, the drought simulations with reduced values of groundwater recharge and precipitation, the year 2012 and the average annual precipitation and groundwater recharge from 1981 - 2010 from the new data sources. The model input data that were used to make the prediction maps are within a zipped folder (Prediction_Input_Data.zip) that contains 50 files, one for each model predictor variable. These include the predictor variables from the original model as well as the updated precipitation and groundwater recharge variables for the year 2012 and the average annual values based on the years1981 - 2010, and groundwater recharge and precipitation variables that were systematically decreased for drought simulations. The model prediction outputs are within a zipped folder (Prediction_Output_Data.zip) that contains 10 tif-format raster files, one for each of the eight drought simulations, one for the year 2012, and one for the updated average annual precipitation and groundwater recharge variables for 1981 - 2010. A third zipped folder (Change_Prob_Maps.zip) contains 10 tif-raster files that show the change in probability of arsenic exceeding 10 micrograms per liter in private domestic wells based on the drought simulations and the data used for the year 2012.

This data release contains data used to develop models and maps that estimate probabilities of exceeding various thresholds of arsenic concentrations in private domestic wells throughout the conterminous United States. Three boosted regression tree (BRT) models were developed separately to estimate the probability of private well arsenic concentrations exceeding 1, 5, and 10 micrograms per liter (µg/L). A random forest (RF) model was developed to estimate the most probable arsenic concentration category (≤5, >5 to ≤10, or >10 µg/L). The models use arsenic concentration data from private domestic wells located throughout the conterminous United States and independent variables that are available as geospatial data. The models were used to produce maps that are included in this data release. The model input data (predictor variables) that were used to make the maps are within a zipped folder (Map_Input_Data.zip) that contains 85 tif-raster files, one for each model predictor variable. The map probability estimates that are outputs from the model are in a zipped folder (Map_Output_Data.zip) that contains 13 tif-raster files, one model estimate map for each of the BRT models and four for the RF model, as well as 2 confidence interval maps for each BRT model.

This data release contains data used to develop models and maps that estimate probabilities of exceeding various thresholds of arsenic concentrations in private domestic wells throughout the conterminous United States. Three boosted regression tree (BRT) models were developed separately to estimate the probability of private well arsenic concentrations exceeding 1, 5, and 10 micrograms per liter (µg/L). A random forest (RF) model was developed to estimate the most probable arsenic concentration category (≤5, >5 to ≤10, or >10 µg/L). The models use arsenic concentration data from private domestic wells located throughout the conterminous United States and independent variables that are available as geospatial data. The models were used to produce maps that are included in this data release. The model input data (predictor variables) that were used to make the maps are within a zipped folder (Map_Input_Data.zip) that contains 85 tif-raster files, one for each model predictor variable. The map probability estimates that are outputs from the model are in a zipped folder (Map_Output_Data.zip) that contains 13 tif-raster files, one model estimate map for each of the BRT models and four for the RF model, as well as 2 confidence interval maps for each BRT model.

Arsenic concentrations from 20,450 domestic wells in the U.S. were used to develop a logistic regression model of the probability of having arsenic > 10 µg/L (“high arsenic”), which is presented at the county, state, and national scales. Variables representing geologic sources, geochemical, hydrologic, and physical features were among the significant predictors of high arsenic. For U.S. Census blocks, the mean probability of arsenic > 10 µg/L was multiplied by the population using domestic wells to estimate the potential high-arsenic domestic-well population. Approximately 44.1 M people in the U.S. use water from domestic wells. The population in the conterminous U.S. using water from domestic wells with predicted arsenic concentration > 10 µg/L is 2.1 M people (95% CI is 1.5 to 2.9 M). Although areas of the U.S. were underrepresented with arsenic data, predictive variables available in national datasets were used to estimate high arsenic in unsampled areas. Linking predictive modeling to private well use information nationally, despite the uncertainty, is beneficial for broad screening of the population at risk from elevated arsenic in drinking water from private wells. This dataset represents modeled probabilities of arsenic > 10 micrograms per liter in domestic wells in the U.S.

Arsenic concentrations from 20,450 domestic wells in the U.S. were used to develop a logistic regression model of the probability of having arsenic > 10 µg/L (“high arsenic”), which is presented at the county, state, and national scales. Variables representing geologic sources, geochemical, hydrologic, and physical features were among the significant predictors of high arsenic. For U.S. Census blocks, the mean probability of arsenic > 10 µg/L was multiplied by the population using domestic wells to estimate the potential high-arsenic domestic-well population. Approximately 44.1 M people in the U.S. use water from domestic wells. The population in the conterminous U.S. using water from domestic wells with predicted arsenic concentration > 10 µg/L is 2.1 M people (95% CI is 1.5 to 2.9 M). Although areas of the U.S. were underrepresented with arsenic data, predictive variables available in national datasets were used to estimate high arsenic in unsampled areas. Linking predictive modeling to private well use information nationally, despite the uncertainty, is beneficial for broad screening of the population at risk from elevated arsenic in drinking water from private wells. This dataset represents modeled probabilities of arsenic > 10 micrograms per liter in domestic wells in the U.S.

The U.S. Geological Survey (USGS), in cooperation with the U.S. Centers for Disease Control and Prevention and the Maine Center for Disease Control and Prevention, assessed the physical and chemical characteristics and the occurrence, distribution, and oxidation state of inorganic arsenic in drinking water from selected domestic well-water supplies in Maine in 2001–2 and 2006–7. The data collected provide support for evaluating arsenic-removal efficiencies of household water-purification systems and provide information to State and local officials that can be used in determining a water-treatment approach for the removal of arsenic from drinking water.

The U.S. Geological Survey (USGS), in cooperation with the U.S. Centers for Disease Control and Prevention and the Maine Center for Disease Control and Prevention, assessed the physical and chemical characteristics and the occurrence, distribution, and oxidation state of inorganic arsenic in drinking water from selected domestic well-water supplies in Maine in 2001–2 and 2006–7. The data collected provide support for evaluating arsenic-removal efficiencies of household water-purification systems and provide information to State and local officials that can be used in determining a water-treatment approach for the removal of arsenic from drinking water.

The map graphic image at https://www.sciencebase.gov/catalog/file/get/63140561d34e36012efa2b7f?name=arsenic_map.png illustrates arsenic values, in micrograms per liter, for groundwater samples from about 31,000 wells and springs in 49 states compiled by the United States Geological Survey (USGS). The map graphic illustrates an updated version of figure 1 from Ryker (2001). Cited Reference: Ryker, S.J., Nov. 2001, Mapping arsenic in groundwater-- A real need, but a hard problem: Geotimes Newsmagazine of the Earth Sciences, v. 46 no. 11, p. 34-36 at http://www.agiweb.org/geotimes/nov01/feature_Asmap.html. An excel tabular data file, a txt file, along with a GIS shape file of arsenic concentrations (20,043 samples collected by the USGS) for a subset of the sites shown on the map. Samples were collected between 1973 and 2001 and are provided for download.

The map graphic image at https://www.sciencebase.gov/catalog/file/get/63140561d34e36012efa2b7f?name=arsenic_map.png illustrates arsenic values, in micrograms per liter, for groundwater samples from about 31,000 wells and springs in 49 states compiled by the United States Geological Survey (USGS). The map graphic illustrates an updated version of figure 1 from Ryker (2001). Cited Reference: Ryker, S.J., Nov. 2001, Mapping arsenic in groundwater-- A real need, but a hard problem: Geotimes Newsmagazine of the Earth Sciences, v. 46 no. 11, p. 34-36 at http://www.agiweb.org/geotimes/nov01/feature_Asmap.html. An excel tabular data file, a txt file, along with a GIS shape file of arsenic concentrations (20,043 samples collected by the USGS) for a subset of the sites shown on the map. Samples were collected between 1973 and 2001 and are provided for download.

This data release contains a table of measured arsenic concentrations and associated model input variables used to test existing multivariate logistic regression models that predict the probabilities of arsenic concentrations exceeding threshold values of 1, 5, and 10 micrograms per liter in bedrock aquifers of New Hampshire. Location data are censored to the county level.