CAMELSH: A Large-Sample Hourly Hydrometeorological Dataset and Attributes at Watershed-Scale for CONUS.

Journal: Scientific data
Published Date: Jul 28, 2025

Abstract

We present CAMELSH (Catchment Attributes and Hourly HydroMeteorology for Large-Sample Studies), the first large-sample hydrometeorological dataset at the hourly scale for the contiguous United States. CAMELSH intergrates hourly meteorological time series, catchment attributes and boundaries from GAGES-II and HydroATLAS for 9,008 catchments across diverse climatic, hydrological, and anthropogenic conditions. In addition, hourly streamflow time series is provided for 3,166 catchments. The dataset spans 45 years (1980-2024) with 11 meteorological variables from the NLDAS-2 forcing dataset, from which we compute nine climate indices related to precipitation, evapotranspiration, seasonality, and snow fraction. Additionally, CAMELSH includes two sets of catchment attributes: 439 from GAGES-II and 195 derived from HydroATLAS. These attributes include factors related to climate, geology, hydrology, river/stream morphology, landscape, nutrient, soil, topography, and anthropogenic influences. Developed in accordance with FAIR (Findability, Accessibility, Interoperability, and Reusability) principles, CAMELSH is the first large-sample dataset at an hourly timescale, supporting machine learning applications for short-term streamflow (flood) prediction and advancing data-driven hydrological research across multiple timescales.

Authors

  • Vinh Ngoc Tran
    Department of Civil and Environmental Engineering, University of Michigan, Ann Arbor, MI, USA. vinhtn@umich.edu.
  • Donghui Xu
    Atmospheric, Climate, & Earth Sciences Division, Pacific Northwest National Laboratory, Richland, WA, 99354, USA.
  • Tam Van Nguyen
    Department of Hydrogeology, Helmholtz Centre for Environmental Research - UFZ, Leipzig, Germany.
  • Taeho Kim
    Department of Radiation Oncology, Washington University in St. Louis, St Louis, MO, 63110, USA.
  • Valeriy Y Ivanov
    Department of Civil and Environmental Engineering, University of Michigan, Ann Arbor, MI, USA. ivanov@umich.edu.

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