CCAM: China Catchment Attributes and Meteorology dataset

[摘要] The absence of a compiled large-scale catchmentcharacteristics dataset is a key obstacle limiting the development of large-sample hydrology research in China. We introduce the first large-scalecatchment attribute dataset in China. We compiled diverse data sources,including soil, land cover, climate, topography, and geology, to develop thedataset. The dataset also includes catchment-scale 31-year meteorologicaltime series from 1990 to 2020 for each basin. Potential evapotranspirationtime series based on Penman's equation are derived for each basin. The 4911catchments included in the dataset cover all of China. We introduced severalnew indicators that describe the catchment geography and the underlyingsurface differently from previously proposed datasets. The resulting datasethas a total of 125 catchment attributes and includes a separate HydroMLYR (hydrology dataset for machine learning in the Yellow River Basin)dataset containing standardized weekly averaged streamflow for 102 basins inthe Yellow River Basin. The standardized streamflow data should be able tosupport machine learning hydrology research in the Yellow River Basin. Thedataset is freely available at https://doi.org/10.5281/zenodo.5729444 (Zhen et al., 2021). Inaddition, the accompanying code used to generate the dataset is freelyavailable at https://github.com/haozhen315/CCAM-China-Catchment-Attributes-and-Meteorology-dataset (last access: 26 November 2021)and supports the generation of catchment characteristics for any custombasin boundaries. Compiled data for the 4911 basins covering all of Chinaand the open-source code should be able to support the study of any selectedbasins rather than being limited to only a few basins.

[学科分类] 眼科学