Articles | Volume 13, issue 12
https://doi.org/10.5194/essd-13-5591-2021
https://doi.org/10.5194/essd-13-5591-2021
Data description paper
 | 
03 Dec 2021
Data description paper |  | 03 Dec 2021

CCAM: China Catchment Attributes and Meteorology dataset

Zhen Hao, Jin Jin, Runliang Xia, Shimin Tian, Wushuang Yang, Qixing Liu, Min Zhu, Tao Ma, Chengran Jing, and Yanning Zhang

Data sets

CCAM: China Catchment Attributes and Meteorology dataset Zhen Hao, Jin Jin, Runliang Xia, Shimin Tian, Wushuang Yang, Qixing Liu, Min Zhu, Tao Ma, and Chengran Jing https://doi.org/10.5281/zenodo.5729444

Model code and software

CCAM: China Catchment Attributes and Meteorology dataset Zhen Hao https://doi.org/10.5281/zenodo.5749718

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Short summary
CCAM is proposed to promote large-sample hydrological research in China. The first catchment attribute dataset and catchment-scale meteorological time series dataset in China are built. We also built HydroMLYR, a hydrological dataset with standardized streamflow observations supporting machine learning modeling. The open-source code producing CCAM supports the calculation of custom watersheds.
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