Development of a US national-scale, mixed-source, pesticide, rural well database for use in drinking water risk...

For pesticide registrations in the USA under the Federal Insecticide, Fungicide, and Rodenticide Act (FIFRA), as implemented by the United States Environmental Protection Agency, drinking water risk assessments for groundwater sources are based on standard scenario modeling concentration estimates. The conceptual model for the drinking water protection goals is defined in terms of (1) a rural well in or near a relatively high pesticide use area, a shallow well (4-10 m); (2) long-term, single-station weather data; (3) soils characterized as highly leachable; (4) upper-end or surrogate, worst-case environmental fate parameters; and (5) maximum, annual use rates repeated every year. To date, monitoring data have not been quantitatively incorporated into FIFRA drinking water risk assessment; even though considerable, US national-scale temporal and spatial data for some chemistries exists. Investigations into drinking water monitoring data development have historically focused on single-source efforts that may not represent wide geographies and/or time periods, whereas Safe Drinking Water Act groundwater monitoring data are focused on a community-level scale rather than an individual, shallow, rural well. In the current case study, US national-scale, rural well data for the herbicide atrazine was collected, quality controlled, and combined into a single database from mixed sources (termed the atrazine rural well database) to (1) characterize differences between exposure estimates from standard EPA modeling approaches for specific characterization, (2) evaluate monitoring data toward direct use in US drinking water risk assessments to compliment or supersede standard modeling approaches to define risk, and (3) evaluate monitoring trends a function of time relative to label changes implemented as part of the registration review process. Of the 75,665 drinking water samples collected from groundwater, atrazine was only detected in 3185, a 4% detection rate.