Percentage of basin-fill aquifer model grid cells in the Southwest Principal Aquifers study area that are predicted to exceed the relative background nitrate concentration, by percentage of agricultural and urban land use in the model grid cell ........... 48 12. Standardized importance scores for the prediction and confirmatory random forest classifiers of arsenic concentrations in basin-fill aquifers of the Southwest
Regulatory agencies are becoming increasingly interested in using young-ground water dating techniques, such as the 3H/3He method, in assessing the susceptibility of public supply wells (PSWs) to contamination. However, recent studies emphasize that ground water samples of mixed age may be the norm, particularly from long-screened PSWs, and tracer-based "apparent" ages can differ substantially from actual mean ages for mixed-age samples. We present age and contaminant data from PSWs in Salt Lake Valley, Utah, that demonstrate the utility of 3H and 3He measurements in evaluating well susceptibility, despite potential age mixing. Initial 3H concentrations (measured 3H + measured tritiogenic 3He) are compared to those expected based on the apparent 3H/3He age and the local precipitation 3H record. This comparison is used to determine the amount of modern water (recharged after approximately 1950) vs. prebomb water (recharged before approximately 1950) samples might contain. Concentrations of common contaminants were also measured using detection limits generally lower than those used for regulatory purposes. A clear correlation exists between the potential magnitude of the modern water fraction and both the occurrence and concentration of contaminants. For samples containing dominantly modern water based on their initial 3H concentrations, potential discrepancies between apparent 3H/3He ages and mean ages are explored using synthetic samples that are random mixtures of different modern waters. Apparent ages can exceed mean ages by up to 13 years for these samples, with an exponential age distribution resulting in the greatest discrepancies.
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AbstractHuman-health concerns and economic considerations associated with meeting drinking-water standards motivated a study of the vulnerability of basin-fill aquifers to nitrate contamination and arsenic enrichment in the southwestern United States. Statistical models were developed by using the random forest classifier algorithm to predict concentrations of nitrate and arsenic across a model grid representing about 190,600 square miles of basin-fill aquifers in parts of Arizona, California, Colorado, Nevada, New Mexico, and Utah. The statistical models, referred to as classifiers, reflect natural and human-related factors that affect aquifer vulnerability to contamination and relate nitrate and arsenic concentrations to explanatory variables representing local-and basin-scale measures of source and aquifer susceptibility conditions. Geochemical variables were not used in concentration predictions because they were not available for the entire study area. The models were calibrated to assess model accuracy on the basis of measured values.
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