Assimilation of river discharge in a land surface model to improve estimates of the continental water cycles

Wang, Fuxing; Polcher, Jan; Peylin, Philippe; Bastrikov, Vladislav

doi:https://doi.org/10.5194/hess-22-3863-2018

Articles | Volume 22, issue 7

https://doi.org/10.5194/hess-22-3863-2018

© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Special issue:

Integration of Earth observations and models for global water...

https://doi.org/10.5194/hess-22-3863-2018

© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 22, issue 7

Research article

|

19 Jul 2018

Research article |

| 19 Jul 2018

Assimilation of river discharge in a land surface model to improve estimates of the continental water cycles

Fuxing Wang, Jan Polcher, Philippe Peylin, and Vladislav Bastrikov

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Final revised paper (published on 19 Jul 2018)
Supplement to the final revised paper
Preprint (discussion started on 08 Jan 2018)

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

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- Supplement

RC1: 'Assimilation of river discharge in a land surface model to improve estimates of the continental water cycles', Anonymous Referee #1, 27 Feb 2018
- AC4: 'Response to Comments from Anonymous Reviewer #1', Fuxing Wang, 24 May 2018
RC2: 'Review', Anonymous Referee #2, 16 Apr 2018
- AC3: 'Response to Comments from Anonymous Reviewer #2', Fuxing Wang, 21 May 2018

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

ED: Publish subject to minor revisions (further review by editor) (11 Jun 2018) by Jaap Schellekens

AR by Fuxing Wang on behalf of the Authors (12 Jun 2018) Author's response Manuscript

ED: Publish as is (18 Jun 2018) by Jaap Schellekens

Short summary

This work improves river discharge estimation by taking advantages of observation and model simulations. The new estimation takes into account both gauged and un-gauged rivers, and it compensates model systematic errors and missing processes (e.g., human water usage). This improved estimation is important not only for water resources management and ecosystem health over continent but also for ocean dynamics and salinity.