An analytical method was developed for the simultaneous extraction and determination of 18 fluoroquinolones (FQs), tetracyclines (TCs) and sulfonamides (SAs) antibiotics from soils using solid phase extraction and liquid chromatography-tandem mass spectrometry. The soils were extracted by different solvents with the help of mechanical shaking and ultrasonic treatment at 59 kHz, followed by a strong anion exchange (SAX) cartridge to clean up soil samples and a hydrophilic lipophilic balance (HLB) cartridge as enrichment. The method was evaluated by testing the following variables: extraction solvents, the type of SPE cartridges, solvent volumes, initial spiking levels and soil types (silty clay loam and clay loam soils). The soil extraction method was validated using these two types of soils, representing two typical agricultural soils in northern China. For 2 g soil, the extraction steps with the mixture of potassium phosphate buffer and acetonitrile (ACN) (1/1, v/v, pH 3.2) provided satisfactory recoveries. In the clay loam soil, the recoveries of all the compounds were from 56% to 89% at the spiking level of 50 µg kg⁻¹ soil, and from 69% to 97% at the spiking level of 200 µg kg⁻¹ soil, respectively. Recoveries in silty clay loam soil were similar to that in clay loam. The method was successfully employed using soil samples collected from a farmland and afforestion area irrigated with sewage in northern China. The result indicates that trace antibiotics in sewage may accumulate in soil irrigated by river water containing sewage.

Watershed models have gradually been adapted to support both decision and policy making for global environmental pollution control. In this study, two watershed models with different complexity, the Soil and Water Assessment Tool (SWAT) and the Generalized Watershed Loading Function (GWLF), were applied in two catchments in data scarce China, namely the Tunxi and the Hanjiaying basins with contrasting climatic conditions (humid and semi-arid, respectively). The performances of both models were assessed via comparison between simulated and measured monthly streamflow, sediment yield, and total nitrogen. Time series plots as well as four statistical measures (the coefficient of determination (R²), the Nash–Sutcliffe efficiency (NSE), percent bias (PBIAS), and RMSE (root mean square error)—observations standard deviation ratio (RSR)) were used to estimate the performance of both models. The results show that both models were generally able to simulate monthly streamflow, sediment, and total nitrogen loadings during the simulation period. However, SWAT performed better for detailed representations, while GWLF could produce much better average values of the observed data. Thus, GWLF offers a user-friendly prospective alternative watershed model that requires little input data and that is applicable for areas where the input data required for SWAT are not always available. SWAT is more suitable for projects that require high accuracy and offers an advantage when measured data are scarce.