Taking a high frequency pulse of rivers: the new wave of water-quality and pollution checks to support integrated real-time river basin management.

人口密集的河流集水区的城市水污染和质量问题是地球上社会面临的最紧迫的环境和公共卫生挑战之一，影响生态系统功能以及水和粮食安全。最近在实地环境分析监测能力方面取得的进展使人们首次了解到城市和城市周边地区水污染问题的高度动态变化。这些措施包括确定热点，即污染程度增加的地区和炎热的时刻，即严重污染的时期，过度影响集水水质。然而，这些污染热点和热点时刻的相对重要性以及导致这种行为的条件尚未确定。我们目前正在经历一场环境监测技术革命，将水质和污染传感的范式改变到新的领域，为掌握复杂景观中水质极端情况的脉搏提供了前所未有的机会。最近的传感器革命使现场水质监测成为可能，而不是在现场采集水样并将其运回实验室进行后续分析，也就是说，实时和直接地监测水质。这些技术进步使得能够更充分地捕捉动态流量和污染事件的事件特征，包括水质极端事件。最近的跨学科研究也引发了对河流流域污染源区激活识别的有用指标的开发。本项目将在这些发展的最前沿工作，直接改善我们检测，监测和预防城市河流污染的方式。这个博士项目将开创新型水质传感器网络和数值模型的组合和综合开发，以提高对沿着城乡梯度源区活化演变的机械理解。因此，它将推动当前原位水质监测技术（如吸光度和荧光探针）的范例，以及流域尺度的水质监测，以确定污染源的事件动态（图1右）。这项研究的结果将直接支持发展更多的基于证据的预测和管理的河流流域管理。

Urban water pollution and quality concerns within densely populated river catchments are amongst the most pressing environmental and public health challenges faced by societies on the planet, impacting ecosystem functioning and water and food security. Recent advances in field-based environmental analytical monitoring capacity have yielded first insights into the highly dynamic behaviour of water pollution problems in urban and peri-urban places. These include the identification of hotspots, as areas of increased pollution levels and hot moments, as periods of intensive pollution, that over-proportionally affect catchment water quality. However, the relative importance of these pollution hotspots and hot moments as well as the conditions that cause this behaviour have yet to be determined.We are currently experiencing a technological revolution in environmental monitoring, changing paradigms in water quality and pollution sensing to new frontiers that open unprecedented opportunities for taking the pulse of water quality extremes in complex landscapes. Instead of taking water samples in the field and transporting them back into the laboratory for subsequent analysis, the recent sensor revolution enables the monitoring of water quality in-situ, that is, in real-time and directly where it occurs. These technological advances enable to more adequately capture the event characteristics of dynamic flow and pollution events, including water quality extremes. Recent interdisciplinary research has also triggered the development of useful metrics for the identification of pollution source zone activation in river basins.This project will work at the forefront of these developments to directly improve the way we detect, monitor, and prevent pollution of urban rivers. This PhD project will pioneer the combined and integrated development of novel types of water quality sensor networks and numerical models of in order improve the mechanistic understanding of the evolution of source area activation along urban-rural gradients. It will therefore push current paradigms in in-situ water quality monitoring technologies (such as absorbance and fluorescence probes, as well as river basin scale water quality monitoring in order to identify event-based dynamics of pollution sources (Figure 1 right). The findings of this study will directly support the development of more evidence-based prediction and management of river basin management.