Coxon, Gemma
ORCID: https://orcid.org/0000-0002-8837-460X; Zheng, Yanchen
ORCID: https://orcid.org/0000-0002-2212-9134; Barbedo, Rafael
ORCID: https://orcid.org/0000-0002-3910-9244; Cooper, Hollie
ORCID: https://orcid.org/0000-0002-1382-3407; Fileni, Felipe; Fowler, Hayley J.
ORCID: https://orcid.org/0000-0001-8848-3606; Fry, Matthew
ORCID: https://orcid.org/0000-0003-1142-4039; Green, Amy; Gribbin, Tom; Harfoot, Helen; Lewis, Elizabeth
ORCID: https://orcid.org/0000-0002-7471-9988; Neto, Germano Gondim Ribeiro
ORCID: https://orcid.org/0000-0002-0823-0885; Qiu, Xiaobin; Salwey, Saskia
ORCID: https://orcid.org/0000-0002-2100-3142; Wendt, Doris E..
2026
CAMELS-GB v2: hydrometeorological time series and landscape attributes for 671 catchments in Great Britain.
Earth System Science Data, 18 (6).
4345-4371.
10.5194/essd-18-4345-2026
Large-sample hydrological datasets containing data for tens to thousands of catchments are invaluable for hydrological process understanding and modelling. CAMELS (Catchment Attributes and MEteorology for Large-sample Studies) datasets provide hydro-meteorological timeseries, catchment attributes and catchment boundaries. Here, we present the second version of CAMELS-GB. CAMELS-GB v2 collates millions of observations from across Great Britain at hourly to monthly timescales, including quality-controlled daily river flows, catchment boundaries, and catchment characteristics from the UK National River Flow Archive. The new features include (1) extended daily hydro-meteorological timeseries from 1970–2022 including meteorological timeseries from new observed climate datasets, (2) hourly precipitation, river flow and level timeseries, (3) groundwater level timeseries and attributes for 55 groundwater wells, and (4) new catchment attributes characterising changing land cover, peak flows and human influences. These data are provided for 671 catchments across Great Britain spanning a diverse range of geophysical characteristics and human influences. CAMELS-GB v2 represents a step change for environmental and modelling analyses across Great Britain, particularly for the characterisation of sub-daily hydrological processes, and is made available as an open dataset (Coxon et al., 2025; https://doi.org/10.5285/9a46d428-958f-4ac1-86eb-94eee70c0955).
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