the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 27 Nov 2025
CAMELS-GB v2: hydrometeorological time series and landscape attributes for 671 catchments in Great Britain
Abstract. 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) new hourly precipitation, river flow and level timeseries, (3) new 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).
- Preprint
(1492 KB) - Metadata XML
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Supplement
(1515 KB) - BibTeX
- EndNote
Status: open (until 31 Jan 2026)
- RC1: 'Comment on essd-2025-608', Yi He, 29 Dec 2025 reply
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RC2: 'Comment on essd-2025-608', Alexander Dolich, 08 Jan 2026
reply
Thank you for your work in compiling CAMELS-GB v2 and this manuscript. The data is very nicely formatted and the addition of hourly hydro-meteorological timeseries data is extremely valuable to expand the field of large-sample hydrology to sub-daily resolutions. The addition of groundwater data and the extensive quality control of hourly streamflow data is also very valuable and outstanding among other CAMELS datasets. The extension of the daily timeseries length and the expansion of the catchment attributes, especially the changing land cover attributes, are also of great value and show the author's motivation and dedication to maintain and update CAMELS-GB.
The manuscript gives a very detailed and thorough description of the dataset while highlighting its importance and also describing its limitations. I recommend accepting the manuscript after minor revisions.I think the accessibility of the dataset could be enhanced by offering the option to easily download a compressed file containing the entire dataset. A more detailed explanation of this as well as minor comments and technical corrections can be found in the attached PDF file.
Data sets
Catchment boundaries, daily and sub-daily hydrometeorological time series, groundwater level time series and attributes for 671 catchments in Great Britain (CAMELS-GB v2) Gemma Coxon et al. https://doi.org/10.5285/8344e4f3-d2ea-44f5-8afa-86d2987543a9
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- 1
This manuscript presents a major and valuable update to the CAMELS-GB large-sample hydrological dataset. The inclusion of extended daily records, national-scale hourly rainfall and flow data, groundwater level time series, dynamic land-cover attributes, and enhanced hydrometric and human-influence metadata represents a substantial contribution to the hydrological and Earth system science communities. The manuscript is well written and clearly structured. The dataset is openly available, well documented, and likely to see wide uptake. I recommend acceptance subject to minor revisions.
Major comments
1. Visibility of key methodological details
Several important methodological aspects are described in the Supplementary Information, including propagation and prioritisation of quality-control flags; identification and documentation of suspected outliers and datum changes in groundwater level time series; inter-comparisons between meteorological products at daily and hourly scales. Some of this information is essential for correct dataset usage and could be more explicitly signposted in the main manuscript, to ensure users are aware of these important safeguards and limitations without needing to discover them independently.
2. Guidance on choice between alternative data products
The dataset provides multiple alternative products for rainfall and PET (e.g. CEH-GEAR vs HadUK-Grid; CEH-GEAR1hr vs GRaD-GB(1H1K)), which is a clear strength. The manuscript and Supplement provide quantitative comparisons between these products. But the manuscript would benefit from more explicit user guidance on dataset selection. For example:
3. Interpretation of extrapolated peak flows and discharge uncertainty
The manuscript explains (L354-357) that discharge uncertainties were recalculated using longer streamflow time series but the same methodological framework as Coxon et al. (2015). However, it remains unclear why the uncertainty estimates are described in L369 as being based on an ‘older set of gaugings’, and why newer gauging information was not incorporated. Please clarify this distinction and its implications for peak-flow analyses.
Please clarify how the percentage of time exceeding the maximum gauged flow is calculated (e.g. proportion of valid daily/hourly timesteps) in Fig5.
Minor Comments
L111 " Mean daily averages calculated from 1st October 1970 – 30th September 2022 for the 671 CAMELS-GB catchments." , ‘mean’ and ‘average’ are synonymous. Do the authors mean daily averages that were then averaged again? The sentence also misses a verb.
L323 “increasing land cover over time” should be “increasing urban land cover over time”
L369-371: The sentence is difficult to follow. I suggest clarifying that the uncertainty bounds are derived from an older gauging dataset and may not fully capture uncertainty at extreme flows.
L386-387: The sentence structure seems odd and needs rephrasing.
L444-445: It states that ten catchments have a normalised upstream capacity greater than 0.25. However, based on the released file “camels_gb_v2_humaninfluence_attributes.csv”, only nine catchments >0.25. Please check and correct this number to ensure consistency between the manuscript and the dataset. The threshold of 0.25 used to highlight catchments with large normalised upstream capacity is not explained. Please justify the choice of 0.25.