Key project stats
The challenge
Under the Water Framework Directive, 86% of UK rivers fail to meet ‘good’ ecological status, with evidence suggesting that three in four rivers may pose a potential risk to human health.
The water industry continues to invest heavily in catchment management to improve water quality at source while addressing the growing pressures of population growth and climate change. Although monitoring capabilities have expanded, the sector faces a critical challenge:
- Managing and analysing increasingly large volumes of data
- Identifying cost-effective approaches to extract actionable insights
- Turning complex datasets into informed, timely decision-making
The solution
Through the River Deep Mountain AI project, a suite of open-source, scalable digital models was developed to support proactive water quality management across the sector.
Funded by the Ofwat Innovation Fund and led by Northumbrian Water, the collaboration harnessed expertise from across the industry including UK water companies, consultants, non-governmental organisations and regulators.
WRc played a key role by contributing scientific knowledge and domain expertise on river water quality, catchment management and data science, ensuring that each model is, scientifically robust, operationally relevant aligned with real-world catchment management challenges. These models leverage AI and remote sensing technologies to provide new insights into pollution sources, behaviours, and risks.
Project partners
ADAS, Anglian Water, Cognizant, Dŵr Cymru Welsh Water, Northern Ireland Water, Northumbrian Water, South West Water, Stream, The Rivers Trust, Uisce Éireann, Water Research Centre Limited, Wessex Water, Xylem Inc.