Xie Hui, Shang Meiqi, Dong Jianwei, Li Yunliang, Lai Xijun
Key Laboratory of Lake and Watershed Science for Water Security, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China; Poyang Lake Wetland Research Station, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Jiujiang 332899, China.
Key Laboratory of Lake and Watershed Science for Water Security, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China; School of Marine Science and Engineering, Nanjing Normal University, Nanjing 210023, China.
J Hazard Mater. 2025 Feb 5;483:136681. doi: 10.1016/j.jhazmat.2024.136681. Epub 2024 Nov 26.
A lack of hydro-biogeochemical models for catchment-scale antibiotic dynamics limits our mechanistic understanding of the transport and fate of antibiotics. This study addresses this gap by developing a distributed and process-based model that focuses on the complex water-sediment-antibiotic interactions. We applied the model to a typical agricultural catchment and selected tetracyclines (TCs) as the target antibiotics. Parameter sensitivity analysis demonstrated that source distribution, groundwater discharge, and water-soil/sediment partitioning were crucial processes. The multi-site performance evaluation generally proved the model's validity, though some overestimation of riverine concentration dynamics was observed. The grid-based distribution of the annual source inputs of the summation of the four TCs (∑TCs) highly varied in space (μ = 3494.92 mg·ha·yr, σ = 4761.20 mg·ha·yr). About 99 % of the source inputs were retained in soil, with mixing layer as the largest reservoir and degradation as the primary loss pathway. Daily terrestrial discharged loading of ∑TCs peaked with rainfall events. Surface runoff contributed more than 50 % of the terrestrial load of ∑TCs in summer, while groundwater discharge dominated in other seasons. These results imply that the catchment-scale TCs dynamics are transport-limited rather than source-limited. Our model offers new insights into the high-resolution sources-transport-fate of antibiotics, aiding in developing strategies to mitigate antibiotic contamination.
缺乏用于流域尺度抗生素动态变化的水文生物地球化学模型，限制了我们对抗生素迁移和归宿的机理理解。本研究通过开发一个基于过程的分布式模型来填补这一空白，该模型聚焦于复杂的水-沉积物-抗生素相互作用。我们将该模型应用于一个典型的农业流域，并选择四环素（TCs）作为目标抗生素。参数敏感性分析表明，源分布、地下水排放以及水-土壤/沉积物分配是关键过程。多站点性能评估总体上证明了该模型的有效性，不过观察到对河流浓度动态存在一些高估。四种TCs总和（∑TCs）的年度源输入的基于网格的分布在空间上变化很大（μ = 3494.92 mg·ha·yr，σ = 4761.20 mg·ha·yr）。约99 %的源输入保留在土壤中，混合层是最大的储存库，降解是主要的损失途径。∑TCs的每日陆地排放负荷在降雨事件时达到峰值。夏季，地表径流对∑TCs陆地负荷的贡献超过50 %，而在其他季节，地下水排放占主导。这些结果表明，流域尺度的TCs动态变化是迁移受限而非源受限。我们的模型为抗生素的高分辨率源-迁移-归宿提供了新见解，有助于制定减轻抗生素污染的策略。
