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

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Cited articles

Abrams, M., Crippen, R., and Fujisada, H.: ASTER global digital elevation model (GDEM) and ASTER global water body dataset (ASTWBD), Remote Sensing, 12, 1156, https://doi.org/10.3390/rs12071156, 2020. 
Addor, N., Newman, A. J., Mizukami, N., and Clark, M. P.: The CAMELS data set: catchment attributes and meteorology for large-sample studies, Hydrol. Earth Syst. Sci., 21, 5293–5313, https://doi.org/10.5194/hess-21-5293-2017, 2017. 
Addor, N., Do, H. X., Alvarez-Garreton, C., Coxon, G., Fowler, K., and Mendoza, P. A.: Large-sample hydrology: recent progress, guidelines for new datasets and grand challenges, Hydrolog. Sci. J., 65, 712–725, 2020. 
Alvarez-Garreton, C., Mendoza, P. A., Boisier, J. P., Addor, N., Galleguillos, M., Zambrano-Bigiarini, M., Lara, A., Puelma, C., Cortes, G., Garreaud, R., McPhee, J., and Ayala, A.: The CAMELS-CL dataset: catchment attributes and meteorology for large sample studies – Chile dataset, Hydrol. Earth Syst. Sci., 22, 5817–5846, https://doi.org/10.5194/hess-22-5817-2018, 2018. 
Belward, A. S., Estes, J. E., and Kline, K. D.: The IGBP-DIS global 1-km land-cover data set DISCover: A project overview, Photogramm. Eng. Rem. S., 65, 1013–1020, 1999. 
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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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