Watershed exposure caused by the use of pesticide in farmland has become a major environmental concern. Currently, there are two major approaches to quantify the watershed exposure: monitoring and modeling. Watershed monitoring is expensive, and short-term monitoring is difficult to be used to address potential long-term exposure variability. Model simulation is widely used because not only can it save time and efforts, but it can also simulate the environmental transport process of pesticide over a long time frame to better understand temporal variability. Research on application of commonly used pesticide exposure assessment models such as PRZM, RICEWQ on watershed scale has found that those models need to be coupled together with waterbody models to assess pesticide exposure at the watershed level, and they are applied on a single crop in targeted area within a watershed, failing to consider the diversity of regional and watershed cropping conditions. To address pesticide exposure assessment in different waterbodies after application on multiple crops within a watershed, this study coupled PRZM, RICEWQ, and SWAT models simultaneously in North Tiaoxi watershed. PRZM model and RICEWQ model were used to simulate the exposure of pesticides in dryland and rice paddies separately, and the pesticide masses through runoff, overflow, spray drift, and other routes simulated by the above two models were set as the input of SWAT model which could simulate hydrology and pollutant transport at watershed scale. Pesticide use, cropping, hydrology, and watershed data were collected, and parameterized for exposure modeling of carbaryl in the North Tiaoxi River after uses on orchard, corn, and rice within the watershed. Model predictions showed high degree of agreement between the simulated results and the field monitoring data. The coupled PRZM, RICEWQ, and SWAT model could simulate reasonably well pesticide exposures in waterbodies with applications on multiple crops within a watershed.
Keywords: Model; PRZM/RICEWQ/SWAT; Pesticide; Watershed.