Smart sensor networks for tracking the evolution of water pollution hotspots and hot moments through river networks

Planetary boundaries for many legacy and emerging contaminants are exceeded. Moving beyond the “safe operating space” for handling these pollutants means increased risks of tipping points which may irreversibly change the functioning of ecosystems and the services they provide, resulting in severe environmental and public health impacts.

In particular the monitoring and prediction of the strongly nonlinear behaviour of many contaminants, including pollution hotspots (locations) and hot moments (events) that disproportionally affecting catchment water quality when a significant proportion of the contaminant load is mobilised withing river catchments and transported to the river network and then further downstream, remains a significant challenge for state of the art water quality monitoring.

We here present the SMARTWATER environmental sensing platform, integrating sensor technology, network and data science innovations with and mathematical modelling with stakeholder catchment knowledge to we diagnose, understand, predict, and manage the emergence and evolution of water pollution hotspots and hot moments. We highlight how innovations in fluorescence and UV absorbance optical sensing technologies can be utilised for instance to track the drivers of extreme hypoxia events through urban and rural observatories and how the combination of easy to sense water quality proxies widely dispersed across the catchment can help optimising high-utility observational networks with regards to the placements of multi-sensor platforms as well as guiding their operation. Deploying data-science approaches including hysteresis and flushing indexes across a range of low- to higher monitoring locations revealed not only divergences in the sources and their mobilisation of different pollutant types (nutrients, DOM, metals) but also differences in their downstream evolution and spatial footprints through complex (and managed) river networks. Integrating information of the different behaviours of pollutants and functional markers such as tryptophan-like fluorescence and Chlorophyll a helped to identify pollutant specific activated source areas and mobilisation mechanisms, supporting also the development of automated event-triggered in-situ sampling solutions for analysis of emerging pollutants (including microplastics) and microbial analyses that are currently not possible to sense in-situ. Integrating this information highlights drastic differences in the contaminant specific emergence of pollution hotspots and hot moments including their large-scale footprint and longer-term relevance for catchment water pollution.