Assimilating shallow soil moisture observations into land models with a water budget constraint

Dan, Bo; Zheng, Xiaogu; Wu, Guocan; Li, Tao

doi:https://doi.org/10.5194/hess-24-5187-2020

Articles | Volume 24, issue 11

https://doi.org/10.5194/hess-24-5187-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/hess-24-5187-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 24, issue 11

Research article

|

10 Nov 2020

Research article |

| 10 Nov 2020

Assimilating shallow soil moisture observations into land models with a water budget constraint

Bo Dan, Xiaogu Zheng, Guocan Wu, and Tao Li

Download

Final revised paper (published on 10 Nov 2020)
Preprint (discussion started on 03 Feb 2020)

Interactive discussion

Status: closed

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

- Printer-friendly version

- Supplement

RC1: 'Review of "Assimilating Shallow Soil Moisture Observations into Land Models with a Water Budget Constraint" by Dan et al.', Anonymous Referee #1, 25 Mar 2020
- AC1: 'Reply to the comments of Reviewer #1', Guocan Wu, 17 May 2020
RC2: 'Comment on "Assimilating Shallow Soil Moisture Observations into Land Models with a Water Budget Constraint"', Anonymous Referee #2, 02 Apr 2020
- AC2: 'Reply to the comments of Reviewer #2', Guocan Wu, 17 May 2020

Peer-review completion

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

ED: Reconsider after major revisions (further review by editor and referees) (13 Jun 2020) by Shraddhanand Shukla

AR by Guocan Wu on behalf of the Authors (15 Jun 2020) Author's response Manuscript

ED: Referee Nomination & Report Request started (26 Jun 2020) by Shraddhanand Shukla

RR by Anonymous Referee #3 (12 Sep 2020)

ED: Publish subject to minor revisions (review by editor) (12 Sep 2020) by Shraddhanand Shukla

AR by Guocan Wu on behalf of the Authors (20 Sep 2020) Author's response Manuscript

ED: Publish as is (01 Oct 2020) by Shraddhanand Shukla

AR by Guocan Wu on behalf of the Authors (03 Oct 2020) Manuscript

Short summary

Data assimilation is a procedure to generate an optimal combination of the state variable in geoscience, based on the model outputs and observations. The ensemble Kalman filter (EnKF) scheme is a widely used assimilation method in soil moisture estimation. This study proposed several modifications of EnKF for improving this assimilation. The study shows that the quality of the assimilation result is improved, while the degree of water budget imbalance is reduced.