In cooperation with the Centers for Disease Control and Prevention (CDC), the U.S. Geological Survey recently developed a statistical model to predict the probability of elevated arsenic levels (>10 mg/L) in domestic wells located throughout the continental United States (CONUS). The arsenic model uses geologic, geochemical, hydrologic, and physical landscape features, available at the national scale as GIS coverages, to predict the probability of high arsenic. Using thirty-year average annual climate and hydrogeologic data, the arsenic model predicts an estimated 2.1 million people in the CONUS use water from a domestic well with an arsenic concentration above the EPA MCL. Average annual precipitation and groundwater recharge are important predictor variables in the model, which suggests that drought conditions may affect the likelihood of elevated arsenic concentrations.
To evaluate the impact of drought, we incorporated precipitation and recharge values from the year 2012, an historical period of large scale drought in the CONUS, into the model in predictive mode. We assessed changes in the probability of elevated arsenic levels and compared with estimates of domestic well water use derived from U.S. Census data. This comparison results in an estimate of potential changes in the population exposed to elevated arsenic under persistent drought conditions. Preliminary results indicate that drought conditions increase the probability of elevated arsenic in private wells used for domestic drinking water, also increasing the total estimated population exposed to high levels of arsenic. This conclusion makes some assumptions including that the arsenic model, which was developed using long term precipitation and groundwater recharge predictor variables, can be extrapolated to drought conditions of shorter duration. Another assumption is that the concentrations of arsenic in domestic groundwater wells, which are typically shallow, respond rapidly to a decrease in precipitation and groundwater recharge. Including drought related variables in arsenic modeling can identify populations susceptible to increased arsenic levels specifically during drought conditions. Understanding the impact of drought on arsenic levels in domestic drinking water wells is an initial step in a process that will allow public health officials to target intervention strategies to reduce exposure and prevent potential adverse health effects in susceptible communities.