Articles | Volume 21, issue 7
https://doi.org/10.5194/hess-21-3267-2017
https://doi.org/10.5194/hess-21-3267-2017
Research article
 | 
04 Jul 2017
Research article |  | 04 Jul 2017

Multi-source hydrological soil moisture state estimation using data fusion optimisation

Lu Zhuo and Dawei Han

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Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
ED: Publish subject to minor revisions (further review by Editor) (10 Apr 2017) by Alexander Gelfan
AR by Lu Zhuo on behalf of the Authors (11 Apr 2017)  Author's response    Manuscript
ED: Publish subject to minor revisions (further review by Editor) (13 May 2017) by Alexander Gelfan
AR by Lu Zhuo on behalf of the Authors (17 May 2017)  Author's response    Manuscript
ED: Publish as is (03 Jun 2017) by Alexander Gelfan
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Short summary
Reliable estimation of hydrological soil moisture state is of critical importance in operational hydrology to improve the flood prediction and hydrological cycle description. This paper attempts for the first time to build a soil moisture product directly applicable to hydrology using multiple data sources retrieved from remote sensing and land surface modelling. The result shows a significant improvement of the soil moisture state accuracy; the method can be easily applied in other catchments.