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

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.