This study brings together extensive, multi-annual groundwater monitoring datasets from the UK and Midwestern US to test the relative importance of site (e.g. land use, soil and aquifer type) and chemical factors (e.g. solubility in water) and between and within year variations in controlling groundwater contamination by pesticides. ANOVA (general linear modelling) was used to test the significance and proportion of variation explained by each factor and their interactions. Results from both the UK and US datasets show that: (i) Chemical and site factors both have a statistically significant influence on groundwater pollution; (ii) Site factors on their own explain a greater proportion of data variance than chemical factors on their own; (iii) Interaction between site and chemical factors represents the most important control on the occurrence of pesticides in groundwater; (iv) Variation within the year was slight but still significant while there was no significant difference between data from consecutive years. The combination of factors analysed in this study were sufficient to explain the majority of the variation in the data save for that ascribable to the analytical detection limit. The results provide statistical evidence that it is viable to develop both molecular methods and groundwater vulnerability as tools to understanding pollution, but that a greater emphasis should be placed on their interaction to fully understand pesticide contamination.