The CAMELS data set:Catchment attributes and meteorology for large-sample studies

Addor, Nans, Newman, Andrew J., Mizukami, Naoki and Clark, Martyn P. (2017) The CAMELS data set:Catchment attributes and meteorology for large-sample studies. Hydrology and Earth System Sciences (HESS), 21 (10). pp. 5293-5313. ISSN 1027-5606

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    Abstract

    We present a new data set of attributes for 671 catchments in the contiguous United States (CONUS) minimally impacted by human activities. This complements the daily time series of meteorological forcing and streamflow provided by Newman et al. (2015b). To produce this extension, we synthesized diverse and complementary data sets to describe six main classes of attributes at the catchment scale: Topography, climate, streamflow, land cover, soil, and geology. The spatial variations among basins over the CONUS are discussed and compared using a series of maps. The large number of catchments, combined with the diversity of the attributes we extracted, makes this new data set well suited for large-sample studies and comparative hydrology. In comparison to the similar Model Parameter Estimation Experiment (MOPEX) data set, this data set relies on more recent data, it covers a wider range of attributes, and its catchments are more evenly distributed across the CONUS. This study also involves assessments of the limitations of the source data sets used to compute catchment attributes, as well as detailed descriptions of how the attributes were computed. The hydrometeorological time series provided by Newman et al.

    Item Type: Article
    Faculty \ School: Faculty of Science > School of Environmental Sciences
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    Depositing User: Pure Connector
    Date Deposited: 14 Nov 2017 06:05
    Last Modified: 14 Nov 2017 06:05
    URI: https://ueaeprints.uea.ac.uk/id/eprint/65434
    DOI: 10.5194/hess-21-5293-2017

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