Emission estimation and fate modelling of three typical pesticides in Dongjiang River basin, China.

Pesticides are widely and intensively used in the world for crops protection. High pesticide loadings can potentially pollute the water resource. However, little is known about the usage, environmental emission and fate of pesticides in river basins. Here, we firstly established a pesticide emission estimation method, and investigated the environmental fate of three commonly used pesticides (chlorpyrifos, triazophos, and isoprothiolane) in Dongjiang River basin, southern China using mathematical modelling approach in combination with field monitoring. The distributed hydrological model SWAT (Soil and Water Assessment Tool) was applied to model the emission of the target pesticides from farmland to stream water, and their fate in the basin. A satisfactory model calibration for flow and suspended sediment was obtained based on eight-year observation data of four hydrological monitoring stations in Dongjiang River basin. The differences between the simulation and observation of pesticides were almost within an order of magnitude, including more than 53% differences within 0.5 order of magnitude. In the river basin, 78860 kg of chlorpyrifos, 54990 kg of triazophos and 35320 kg of isoprothiolane were sprayed onto the crops, the estimated annual emissions of the basin come up to 1801 kg, 3779 kg, and 2330 kg under the conditions of rainfall, surface runoff and percolation. After a series of environmental processes including settlement and degradation within the channels, the predicted export masses for chlorpyrifos, triazophos and isoprothiolane were reduced to 266 kg, 1858 kg, 1350 kg, respectively. Successful prediction suggests that the reliable estimation method combing the SWAT modelling can help us understand the source, concentration levels and fate of pesticides in river basin in different scales. Combing the method of emission and fate modelling method we proposed, countries and regions lacking pesticide-application database can facilitate better management of pesticides.