Predicting regional fluoride concentrations at public and domestic supply depths in basin-fill aquifers of the western United States using a random forest model.

A random forest regression (RFR) model was applied to over 12,000 wells with measured fluoride (F) concentrations in untreated groundwater to predict F concentrations at depths used for domestic and public supply in basin-fill aquifers of the western United States. The model relied on twenty-two regional-scale environmental and surficial predictor variables selected to represent factors known to control F concentrations in groundwater. The testing model fit R2 and RMSE were 0.52 and 0.78 mg/L. Comparisons of measured to predicted proportions of four F-concentrations categories (<0.7 mg/L, 0.7-2 mg/L, >2 mg/L - 4 mg/L, and > 4 mg/L) indicate that the model performed well at making regional-scale predictions. Differences between measured and predicted proportions indicate underprediction of measured F at values by between 4 and 20 mg/L, representing less than 1% of the regional scale predicted values. These residuals most often map to geographic regions where local-scale processes including evaporative discharge in closed basins or intermittent streams concentrate fluoride in shallow groundwater. Despite this, the RFR model provides spatially continuous F predictions across the basin-fill aquifers where discrete samples are missing. Further, the predictions capture documented areas that exceed the F maximum contaminant level for drinking water of 4 mg/L and areas that are below the oral-health benchmark of 0.7 mg/L. These predictions can be used to estimate fluoride concentrations in unmonitored areas and to aid in identifying geographic areas that may require further investigation at localized scales.

Groundwater Quality of Aquifers Overlying the Oxnard Oil Field, Ventura County, California.

Groundwater samples collected from irrigation, monitoring, and municipal supply wells near the Oxnard Oil Field were analyzed for chemical and isotopic tracers to evaluate if thermogenic gas or water from hydrocarbon-bearing formations have mixed with surrounding groundwater. New and historical data show no evidence of water from hydrocarbon-bearing formations in groundwater overlying the field. However, thermogenic gas mixed with microbial methane was detected in 5 wells at concentrations ranging from 0.011-9.1 mg/L. The presence of these gases at concentrations <10 mg/L do not indicate degraded water quality posing a known health risk. Analysis of carbon isotopes (δ13C-CH4) and hydrogen isotopes (δ2H-CH4) of methane and ratios of methane to heavier hydrocarbon gases were used to differentiate sources of methane between a) microbial, b) thermogenic or c) mixed sources. Results indicate that microbial-sourced methane is widespread in the study area, and concentrations overlap with those from thermogenic sources. The highest concentrations of thermogenic gas were observed in proximity to relatively high density of oil wells, large injection volumes of water disposal and cyclic steam, shallow oil development, and hydrocarbon shows in sediments overlying the producing oil reservoirs. Depths of water wells containing thermogenic gas were within approximately 200 m of the top of the Vaca Tar Sand production zone (approximately 600 m below land surface). Due to the limited sampling density, the source and pathways of thermogenic gas detected in groundwater could not be conclusively determined. Thermogenic gas detected in the absence of co-occurring water from hydrocarbon-bearing formations may result from natural gas migration over geologic time from the Vaca Tar Sand or deeper formations, hydrocarbon shows in sediments overlying producing zones, and/or gas leaking from oil-field infrastructure. Denser sampling of groundwater, potential end-members, and pressure monitoring could help better distinguish pathways of thermogenic gases.