Summary
The CAMELS dataset represents a comprehensive synthesis of catchment attributes and meteorological data for 671 minimally disturbed basins across the contiguous United States. By integrating diverse data sources to characterise six major attribute classes at the catchment scale, the authors created a resource designed to support large-sample hydrological studies and comparative hydrology research. The dataset improves upon prior efforts such as MOPEX by incorporating more recent source data, broader attribute coverage, and more spatially even catchment distribution.
UK applicability
Whilst this dataset is US-specific, the methodological approach to synthesising diverse catchment attributes and the framework for comparative hydrology could inform development of similar large-sample datasets for UK river basins. UK hydrological and soil studies might benefit from adopting comparable data integration protocols, though UK catchments differ in geology, climate, and land-use patterns.
Key measures
Catchment-scale attributes including topography, climate, streamflow characteristics, land cover classification, soil properties, and geological features across 671 US catchments
Outcomes reported
The study compiled a dataset of attributes for 671 minimally human-impacted catchments across the contiguous United States, describing six main classes: topography, climate, streamflow, land cover, soil, and geology. This dataset complements daily time series of meteorological forcing and streamflow data, making it suited for large-sample hydrological studies and comparative catchment analysis.
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