Necessary but not sufficient: Exploring the role of diverse water quality datasets in UK river health

The growing availability of water quality datasets presents new opportunities to understand the dynamics of river health across multiple spatial and temporal scales. Citizen scientist data on pollution events, particularly from combined sewage overflows, have successfully increased scrutiny of polluted inland waterways. At the same time, there is a need to avoid undermining the importance of continued high-quality, long-term monitoring. These debates raise a critical question: has increasing data availability translated into improved understanding of, and outcomes for, river health?Based on insights from a scoping review of published academic and grey literature, qualitative case studies from the perspectives of regulators, water companies and wild swimmers, and a systems mapping workshop with interdisciplinary scientists, data providers and users, we examine how existing UK river water quality data are collected and integrated. This combined approach allows us to explore how data are used to support scientific understanding and decision-making by river users and managers across multiple scales.One of the key points made during the workshop was that perceived data gaps may be smaller than initially envisioned if all the data were brought together in one place. As a first step towards improved integration, we will present a systems map and accompanying database of English river datasets and data platforms spanning governmental organisations, private companies, researchers and citizen scientists. These data include CSO spills, faecal indicator organisms, physicochemical variables, macroinvertebrates, major nutrients and other chemical and ecological variables such as microplastics, PFAS and trace elements.Our analysis highlights persistent challenges related to trust, consistency and bias, mismatches between spatial and temporal data resolution and decision needs, limited analytical capacity, and wider political-economic constraints. We argue that while data availability is necessary, it is not sufficient to improve river health. Progress depends not only on continued investment in monitoring, but also on shifting emphasis from identifying data gaps towards improving the integration, interpretation and decision relevance of existing data, enabling more effective understanding of water quality patterns and drivers across scales.