EU Regulation 1107/2009 aims to ensure that pesticides do not pose unacceptable risks to humans, animals, or the environment. Non‐target organisms, such as beneficial insects, birds, and aquatic life, can be adversely affected by pesticide use, so their protection is crucial. Spray drift deposition, where chemicals drift from the target area to surrounding land or water bodies, is a major exposure route. However, this route has not been thoroughly assessed at the European level, considering variations in crops, crop height, farming practices, and agro‐environmental conditions. Mechanistic spray drift models, if appropriately parameterized, offer a way to address these factors and potentially improve upon the German Ganzelmeier‐Rautmann spray drift values used in the current European regulatory risk assessment. This project involved a targeted literature review to identify and assess spray drift deposition models for downward spraying of arable crops against predefined criteria. Among the models identified, the Dutch IDEFICS model was selected for comparative analysis with experimental field trials. IDEFICS computes downwind deposits of spray drift for arable crops with conventional boom sprayers, incorporating variables such as crop type and height, sprayer settings and meteorological conditions. However, IDEFICS has so far been tested and validated only for Dutch conditions, which may not represent the diversity of agricultural and environmental conditions across Europe. To test its wider applicability, five datasets of spray drift experimental data from the EU‐wide SETAC DRAW database and other sources were selected, covering short and tall crops across the three EU regulatory zones. The comparison of simulated and measured spray drift deposition showed that in 72% of the replicates, simulated‐to‐measured deposit ratios were within a reasonable range. Challenges include experimental variability and limited tall crop data. Expanding model evaluations, standardising data collection, and refining testing approaches are recommended to enhance the reliability of mechanistic models in regulatory contexts. © Wageningen University and Research 2025
