The purpose of the present modeling study was to contribute to an improved understanding of the mechanisms involved in pesticide leaching during a single rainfall event with temporal variability. Rainfall intensity of the first event after pesticide application has great effect on the amount of pesticide transported to groundwater and subsurface drains, especially in soils containing preferential flow pathways. One way to improve the understanding of single event properties on pesticide leaching is to use a transport model. The soil–plant–atmosphere model Daisy was used to simulate pesticide leaching during and after single rainfall events of different durations and intensities. Designed temporally variable single rainfall events based on the Chicago Design Rain were inserted in the original weather file. A combination of different intensities (13, 20, 24, 28, 34, and 39 mm h−1) at different event durations (1, 3, 5, and 9 h) where the intensity peak was placed in the middle of the event ware applied, resulting in 24 different design events. The model setup included two different soil types: a coarse sandy soil and a sandy loam containing macropores and subsurface drains. The fates of the herbicides bentazone [3-isopropyl-1H-2,1,3-benzothiadiazin-4(3H)-one 2,2-dioxide] and glyphosate [N-(phosphonomethyl)glycine] were simulated. The leaching dynamics of both pesticides showed high variability at the hourly level, illustrating the importance of high model resolution when estimating pesticide leaching. For the coarse sandy soil different intensities did not appear to have an effect, as pesticide leaching was controlled by event volume. In contrast, results for the sandy loam showed an effect of intensity, especially for glyphosate, at initially wet soil conditions. Short intense events (1 h) resulted in high leaching to drains (1.7% of matrix infiltration) compared to events of longer duration (up to 0.4% of matrix infiltration). This indicates that it might be more prudent to view leaching as a risk that occurs under certain conditions, rather than something that can be averaged.