Articles | Volume 13, issue 12
Earth Syst. Sci. Data, 13, 5591–5616, 2021
https://doi.org/10.5194/essd-13-5591-2021
Earth Syst. Sci. Data, 13, 5591–5616, 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 et al.

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Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CC1: 'Comment on visuals and color maps', Michael Stoelzle, 04 May 2021
    • AC2: 'Reply on CC1', Zhen Hao, 01 Jun 2021
  • RC1: 'Comment on essd-2021-71', Anonymous Referee #1, 01 Jun 2021
    • AC1: 'Reply on RC1', Zhen Hao, 01 Jun 2021
    • AC6: 'Point-by-point reply to Referee 1', Zhen Hao, 16 Aug 2021
  • AC3: 'Comment on essd-2021-71', Zhen Hao, 21 Jun 2021
    • AC4: 'Reply on AC3', Zhen Hao, 22 Jun 2021
  • RC2: 'Comment on essd-2021-71', Anonymous Referee #2, 07 Jul 2021
    • AC7: 'Point-by-point reply to Referee 2', Zhen Hao, 16 Aug 2021
  • AC5: 'Author's general response', Zhen Hao, 10 Aug 2021
  • AC8: 'Update on SURF_CLI_CHN_MUL_DAY', Zhen Hao, 06 Sep 2021

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Zhen Hao on behalf of the Authors (26 Jul 2021)  Author's response    Author's tracked changes    Manuscript
ED: Reconsider after major revisions (16 Aug 2021) by Lukas Gudmundsson
AR by Zhen Hao on behalf of the Authors (16 Aug 2021)  Author's response    Author's tracked changes    Manuscript
ED: Referee Nomination & Report Request started (25 Aug 2021) by Lukas Gudmundsson
RR by Anonymous Referee #1 (19 Sep 2021)
RR by Anonymous Referee #2 (10 Oct 2021)
ED: Publish subject to minor revisions (review by editor) (18 Oct 2021) by Lukas Gudmundsson
AR by Zhen Hao on behalf of the Authors (22 Oct 2021)  Author's response    Author's tracked changes    Manuscript
ED: Publish as is (27 Oct 2021) by Lukas Gudmundsson
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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.