Catchment attributes and hydro-meteorological timeseries for 671 catchments across Great Britain (CAMELS-GB)

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This dataset is available under the terms of the Open Government Licence

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https://doi.org/10.5285/8344e4f3-d2ea-44f5-8afa-86d2987543a9

This dataset provides hydro-meteorological timeseries and landscape attributes for 671 catchments across Great Britain. It collates river flows, catchment attributes and catchment boundaries from the UK National River Flow Archive together with a suite of new meteorological timeseries and catchment attributes. Daily timeseries for the time period 1st October 1970 to the 30th September 2015 are provided for a range of hydro-meteorological data (including rainfall, potential evapotranspiration, temperature, radiation, humidity and flow). A comprehensive set of catchment attributes are quantified describing a range of catchment characteristics including topography, climate, hydrology, land cover, soils, hydrogeology, human influences and discharge uncertainty.

This dataset is intended for the community as a freely available, easily accessible dataset to use in a wide range of environmental data and modelling analyses. A research paper (Coxon et al, CAMELS-GB: Hydrometeorological time series and landscape attributes for 671 catchments in Great Britain) describing the dataset in detail will be made available in Earth System Science Data (https://www.earth-system-science-data.net/).

Publication date: 2020-02-20

12 citations

465 downloads *

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More information

View numbers valid from 01 June 2023 Download numbers valid from 20 June 2024 (information prior to this was not collected)

Formats

Comma-separated values (CSV), Shapefile

Spatial information

Study area

Spatial representation types

Tabular (text)
Vector

Spatial reference system

OSGB 1936 / British National Grid

Temporal information

Temporal extent

1970-10-01 to 2015-09-30

Provenance & quality

CAMELS-GB provides hydro-meteorological timeseries and catchment attributes for 671 catchments.
Catchment meteorological timeseries are derived from CEH-GEAR, CHESS-PE and CHESS-MET. Catchment flow timeseries and boundaries are sourced from the UK National River Flow Archive.

Many of the catchment attributes are sourced either from the National River Flow Archive or from the catchment meteorological timeseries produced in CAMELS-GB. Land cover catchment attributes are derived from the GB 1km percentage target class, Land Cover Map 2015 (Rowland et al, 2017; https://doi.org/10.5285/ee9ab43d-a4fe-4e73-afd5-cd4fc4c82556). Soil catchment attributes are derived from the European Soil Database Derived Data product (Hiederer, 2013a, 2013b), and the modelled depth to bedrock global product (Pelletier et al., 2016). Hydrogeology catchment attributes are derived from the British Geological Survey hydrogeology map (BGS, 2019) and superficial deposits map. Discharge uncertainty estimates for each catchment are derived using the method described in Coxon et al (2015). Human influence catchment attributes were derived from datasets describing ground/surface water abstractions and discharges sourced from the Environment Agency and from datasets describing reservoir capacity and use from the UK reservoir inventory (Durant and Counsell, 2018).

Where possible we have provided quantitative estimates of uncertainty, including timeseries for two potential evapo-transpiration products, percentiles of soil catchment attributes and the first set of national discharge uncertainty estimates. For all datasets we have highlighted the key uncertainties and limitations of the underlying source data products and any methods used to derive the catchment attributes. We hope to raise awareness and encourage users of the dataset to consider these uncertainties in their analyses.

See supporting information for more details.

Licensing and constraints

This dataset is available under the terms of the Open Government Licence

Cite this dataset as:

Coxon, G.; Addor, N.; Bloomfield, J.P.; Freer, J.; Fry, M.; Hannaford, J.; Howden, N.J.K.; Lane, R.; Lewis, M.; Robinson, E.L.; Wagener, T.; Woods, R. (2020). Catchment attributes and hydro-meteorological timeseries for 671 catchments across Great Britain (CAMELS-GB). NERC Environmental Information Data Centre. https://doi.org/10.5285/8344e4f3-d2ea-44f5-8afa-86d2987543a9

BibTeX RIS

Contains Environment Agency information © Environment Agency and/or database right

Derived from UK bedrock hydrogeological mapping and UK superficial productivity mapping, BGS © UKRI

Citations

Coxon, G., Addor, N., Bloomfield, J.P., Freer, J., Fry, M., Hannaford, J., Howden, N.J.K., Lane, R., Lewis, M., Robinson, E.L., Wagener, T., & Woods, R. (2020). CAMELS-GB: hydrometeorological time series and landscape attributes for 671 catchments in Great Britain. Earth System Science Data, 12(4), 2459–2483. https://doi.org/10.5194/essd-12-2459-2020

Kim, K. B., Kwon, H.-H., & Han, D. (2022). Intercomparison of joint bias correction methods for precipitation and flow from a hydrological perspective. In Journal of Hydrology (Vol. 604, p. 127261). Elsevier BV. https://doi.org/10.1016/j.jhydrol.2021.127261

Kratzert, F., Nearing, G., Addor, N., Erickson, T., Gauch, M., Gilon, O., Gudmundsson, L., Hassidim, A., Klotz, D., Nevo, S., Shalev, G., & Matias, Y. (2023). Caravan - A global community dataset for large-sample hydrology. Scientific Data, 10(1). https://doi.org/10.1038/s41597-023-01975-w

Bloomfield, J. P., Gong, M., Marchant, B. P., Coxon, G., & Addor, N. (2021). How is Baseflow Index (BFI) impacted by water resource management practices? Hydrology and Earth System Sciences, 25(10), 5355-5379. https://doi.org/10.5194/hess-25-5355-2021

Zheng, Y., Coxon, G., Woods, R., Li, J., & Feng, P. (2023). A Framework for Estimating the Probability Distribution of Event Runoff Coefficient in Ungauged Catchments. Water Resources Research, 59(1). Portico. https://doi.org/10.1029/2022wr033227

Sawada, Y., Okugawa, S., & Kimizuka, T. (2022). Multi-model ensemble benchmark data for hydrological modeling in Japanese river basins. Hydrological Research Letters, 16(4), 73-79. https://doi.org/10.3178/hrl.16.73

Reaver, N.G.F., Kaplan, D.A., Klammler, H., & Jawitz, J.W. (2022). Theoretical and empirical evidence against the Budyko catchment trajectory conjecture. Hydrology and Earth System Sciences, 26(5), 1507-1525. https://doi.org/10.5194/hess-26-1507-2022

Lees, T., Reece, S., Kratzert, F., Klotz, D., Gauch, M., De Bruijn, J., Kumar Sahu, R., Greve, P., Slater, L., & Dadson, S.J. (2022). Hydrological concept formation inside long short-term memory (LSTM) networks. Hydrology and Earth System Sciences, 26(12), 3079-3101. https://doi.org/10.5194/hess-26-3079-2022

Kiraz, M., Coxon, G. & Wagener, T. (2023) A Signature‐Based Hydrologic Efficiency Metric for Model Calibration and Evaluation in Gauged and Ungauged Catchments. Water Resources Research 59. https://doi.org/10.1029/2023wr035321

Zheng, Y., Coxon, G., Woods, R., Li, J. & Feng, P. (2023) Controls on the Spatial and Temporal Patterns of Rainfall‐Runoff Event Characteristics—A Large Sample of Catchments Across Great Britain. Water Resources Research 59. https://doi.org/10.1029/2022wr033226

Gauch, M. & Lin, J. (2020) A Data Scientist’s Guide to Streamflow Prediction https://doi.org/10.48550/arxiv.2006.12975

Robinson, E.L., Brown, M.J., Kay, A.L., Lane, R.A., Chapman, R., Bell, V.A., & Blyth, E.M. (2023). Hydro-PE: gridded datasets of historical and future Penman–Monteith potential evaporation for the United Kingdom. In Earth System Science Data (Vol. 15, Issue 10, pp. 4433–4461). Copernicus GmbH. https://doi.org/10.5194/essd-15-4433-2023