Optimizing pesticide water monitoring: balancing accuracy and efficiency using composite sampling and SEAWAVE-QEX.

Surface water monitoring is undertaken when characterization of empirically measured levels of pesticides in the environment is necessary and/or desired. While monitoring data can be used to validate exposure models, it is seldom used quantitatively to directly estimate pesticide exposure in regulatory risk assessments due to insufficient sampling frequency. Although daily monitoring is ideal for estimating pesticide exposure in surface water, the costs, resources, and logistics of daily sample collection are prohibitive for most monitoring programs. With the development of statistical tools, such as the United States Geological Survey's Seasonal Wave with Streamflow Adjustment with Extended Capability (SEAWAVE-QEX) model, which can assist with estimating pesticide exposure in surface water using less frequent monitoring data, it is important for monitoring programs to properly evaluate which sampling approach (e.g., sample type and frequency) is most appropriate to satisfy their objectives. To better inform monitoring program design, this study leveraged high-frequency (daily or near-daily) monitoring datasets to assess the performance of extended (weekly and biweekly) composite sampling, as well as weekly and biweekly sampling used in conjunction with SEAWAVE-QEX, to estimate both short-term (acute) and long-term (chronic) pesticide exposure in surface water. Both weekly and biweekly composite sampling were shown to accurately estimate chronic pesticide exposure, whereas a proof-of-concept application of SEAWAVE-QEX using weekly composite sampling reasonably estimated acute exposure at one study site. Precipitation data also proved a viable, cost-saving substitute for streamflow data as a covariate in SEAWAVE-QEX. These findings offer practical guidance for optimizing pesticide water monitoring programs, balancing accuracy and efficiency.