Fileni, F.
ORCID: https://orcid.org/0000-0001-7260-1946; Fowler, H.J.
ORCID: https://orcid.org/0000-0001-8848-3606; Lewis, E.
ORCID: https://orcid.org/0000-0002-7471-9988; Fry, Matthew
ORCID: https://orcid.org/0000-0003-1142-4039; Cooper, Hollie
ORCID: https://orcid.org/0000-0002-1382-3407; Swain, Oliver; Coxon, G.
ORCID: https://orcid.org/0000-0002-8837-460X; McLay, F.; Bruce, E.; Yang, L.
ORCID: https://orcid.org/0000-0003-2115-4909; Archer, D.
ORCID: https://orcid.org/0000-0002-0007-6334.
Sub-hourly river flow data observations from 1369 river gauges in the UK, 1948-2023 (UK-Flow15).
NERC Environmental Information Data Centre
22 October 2025,
https://doi.org/10.5285/211710ac-f01b-4b52-807f-373babb1c368
[Output (Electronic)]
This dataset provides a coherent, quality-controlled collection of 15-minute river flow observations from across the United Kingdom. It brings together more than 1,300 gauging stations and over 50,000 station-years of data collected by the main UK measuring authorities - the Environment Agency (England), Scottish Environment Protection Agency, Natural Resources Wales, the Department for Infrastructure (Northern Ireland), and the UK Centre for Ecology & Hydrology. The records span from 1948 to the present day and represent the first national-scale compilation of sub-daily flow data in a consistent format.
The dataset was created by assembling raw hydrometric records from open APIs and data requests to measuring authorities, then standardising them to a uniform 15-minute time step. A structured quality control framework was applied to identify and flag potential issues such as missing or duplicated values, irregular time steps, and implausible flow events. Each record includes a detailed quality code indicating the outcome of these checks, and a suite of accompanying metadata files provides full traceability of data provenance, quality control results, and any adjustments made during processing.
The resource is designed to support large-sample and national-scale hydrological research, particularly for applications requiring high-resolution data such as flood analysis, catchment response studies, and model calibration.
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