CCAM: China Catchment Attributes and Meteorology dataset

نویسندگان

چکیده

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

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ژورنال

عنوان ژورنال: Earth System Science Data

سال: 2021

ISSN: ['1866-3516', '1866-3508']

DOI: https://doi.org/10.5194/essd-13-5591-2021