Drummond J D, Aquino T, Davies-Colley R J, Stott R, Krause S
University of Birmingham School of Geography, Earth & Environmental Sciences Birmingham UK.
Université de Rennes CNRS Géosciences Rennes, UMR 6118 Rennes France.
Geophys Res Lett. 2022 Apr 28;49(8):e2021GL096514. doi: 10.1029/2021GL096514. Epub 2022 Apr 18.
Rivers transport contaminant microorganisms (including fecal indicator bacteria and human pathogens) long distances downstream of diffuse and point sources, posing a human health risk. We present a mobile-immobile model that incorporates transport as well as immobilization and remobilization of contaminant microbes and other fine particles during baseflow and stormflow. During baseflow conditions, hyporheic exchange flow causes particles to accumulate in streambed sediments. Remobilization of stored particles from streambed sediments occurs slowly during baseflow via hyporheic exchange flow, while remobilization is vastly increased during stormflow. Model predictions are compared to observations over a range of artificial and natural flood events in the dairy contaminated Topehaehae Stream, New Zealand. The model outputs closely matched timing and magnitude of and turbidity observations through multiple high-flow events. By accounting for both state-of-flow and hyporheic exchange processes, the model provides a valuable framework for predicting particle and contaminant microbe behavior in streams.
河流将污染物微生物(包括粪便指示菌和人类病原体)输送到分散源和点源下游的很远距离,对人类健康构成风险。我们提出了一个动静结合模型,该模型纳入了在基流和暴雨径流期间污染物微生物及其他细颗粒的输运、固定和再迁移过程。在基流条件下,潜流交换流会使颗粒在河床沉积物中积累。在基流期间,通过潜流交换流,河床沉积物中储存颗粒的再迁移过程缓慢,而在暴雨径流期间,再迁移则大幅增加。在新西兰受乳制品污染的托佩哈埃哈埃河中,将模型预测结果与一系列人工和自然洪水事件中的观测结果进行了比较。该模型输出结果与多次高流量事件中的沉积物和浊度观测的时间和量级紧密匹配。通过考虑水流状态和潜流交换过程,该模型为预测溪流中颗粒和污染物微生物的行为提供了一个有价值的框架。