Regulatory aquatic exposure modeling at lower tiers typically uses standard scenarios based on assumptions designed to ensure model output is extremely conservative. To improve the accuracy of lower tier exposure assessments, these assumptions need to be examined to prioritize opportunities for refinement. Selected refinements should be quantifiable as numerical distributions of real-world variability which can be incorporated into exposure assessment frameworks via probabilistic modeling. National and regional distributions of landscape-related runoff and drift load transport from treated areas into receiving waters are an important and quantifiable source of variability in lower tier aquatic assessments. Additionally, for uses incorporating multiple aerial applications each season, the real-world co-occurrence of wind speed/direction across sequential seasonal applications has significant and quantifiable variability. The combined effect of these two real-world distributions on probabilistic distributions of potential aquatic pyrethroid exposure is a very significant reduction relative to lower tier predictions. However, other unchanged scenario assumptions ensure the predictions remain conservative.

Refining pyrethroid aquatic exposure assessments by incorporating measured landscape and environmental variability using probabilistic approaches I, overview: Concepts for refining lower tier exposure estimates

248th National Meeting (2014)

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