Diquat dibromide (6,7‐dihydrodipyrido[1,2‐a:2′,1′‐c] pyrazinediium dibromide; diquat) is one of the few herbicides registered for direct application to water systems in the United States to control noxious aquatic weeds. The dissipation of diquat dibromide in aquatic environments is highly dependent on the hydrodynamic and physicochemical characteristics of the receiving water body. Computer simulations (EXAMSII) were conducted to evaluate the variability of diquat cation dissipation in farm ponds, lakes, and canals following applications to control aquatic weeds across the United States. Within each scenario, probabilities were assigned to varying values for physical properties (velocity, dispersion, suspended sediment concentrations, bed sediment properties, and plant biomass) using a joint probability method, and the results were expressed as spatially and temporally explicit cumulative probability distributions by water‐body type on a regional scale. The results showed that the dissipation of diquat cation in water was very rapid, with the highest exposure concentrations (90th percentile) predicted to be 0.194 mg/L diquat cation 1 h after treatment and typically reaching 0.01 mg/L by 96 h.

Pesticides are very important in European rice production. For appropriate environmental protection, it is useful to predict the potential impact of pesticides after application, in paddy fields, in paddy runoff, and in the surrounding water, by calculating predicted environmental concentrations (PECs). In this paper, a joint simulation is described, coupling a field-scale pesticide fate model (RICEWQ) and a transportation model (RIVWQ) to evaluate the potential for predicting environmental concentrations of pesticides in the paddy field and adjacent surface water bodies and comparing the predicted values with the monitoring data. The results demonstrate that the application of the calibrated field-scale RICEWQ model is a conservative method to predict the PEC at the watershed level, overestimating the observed data; the coupled RICEWQ and RIVWQ models could be adequately used to predict PECs in the surrounding water at watershed level and in the higher tier risk assessment procedure.

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