Catchment attributes and meteorology for large sample study in contiguous China

2021 
Abstract. We introduce the first large-scale catchment attributes and meteorological time series dataset of contiguous China. To develop the dataset, we compiled diverse data sources to generate basin-oriented features describing the characteristics of the catchment related to hydrological processes. The proposed dataset consists of catchment characteristics including soil, land cover, climate, topography, geology, and 29-year meteorological time series (from 1990 to 2018). The meteorological variables include precipitation, temperature, evapotranspiration, wind speed, ground surface temperature, pressure, humidity and sunshine duration. We also derived a daily potential evapotranspiration time series based on a modified Penman’s equation. The studied catchments are 4875 catchments within contiguous China derived from digital elevation models. The spatial variations of catchment characteristics are analysed and organized into a series of maps; the correlation analysis between attributes was conducted. Compared to the previously proposed datasets, we derived more catchment characteristics resulting in a total of 127 attributes, providing a complete description of the catchments. Besides, we propose Normal-Camels-YR, a hydrological dataset covering 102 basins of the Yellow River basin with normalized streamflow observations. The proposed dataset provides numerous opportunities for comparative hydrological research, such as examining the difference in hydrological behaviours across different catchments and building general rainfall-runoff modelling frameworks for many catchments instead of limited to a few. The dataset is freely available via http://doi.org/10.5281/zenodo.4704017 for community use. We will open-source the complement code for generating the dataset such that the user can generate meteorological series and catchment attributes for any watershed within contiguous China.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    0
    References
    0
    Citations
    NaN
    KQI
    []