The CAMELS data set: catchment attributes and meteorology for large-sample studies
NSF National Center for Atmospheric Research · University of East Anglia · +1 more institution
Abstract
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…
Citation impact
- FWCI
- 17.40
- Percentile
- 100%
- References
- 75
Authors
4- NANans AddorCorresponding
NSF National Center for Atmospheric Research, University of East Anglia, Research Applications (United States)
- AJAndrew J. NewmanCorresponding
NSF National Center for Atmospheric Research, Research Applications (United States)
- NMNaoki MizukamiCorresponding
NSF National Center for Atmospheric Research, Research Applications (United States)
- MCMartyn ClarkCorresponding
NSF National Center for Atmospheric Research, Research Applications (United States)
Topics & keywords
- Hydrometeorology
- Streamflow
- Sample (material)
- Drainage basin
- Forcing (mathematics)
- Data set
- Land cover
- Hydrology (agriculture)