Articles | Volume 24, issue 10
https://doi.org/10.5194/hess-24-4777-2020
https://doi.org/10.5194/hess-24-4777-2020
Research article
 | 
05 Oct 2020
Research article |  | 05 Oct 2020

Socio-hydrological data assimilation: analyzing human–flood interactions by model–data integration

Yohei Sawada and Risa Hanazaki

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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: Reconsider after major revisions (further review by editor and referees) (06 May 2020) by Giuliano Di Baldassarre
AR by Yohei Sawada on behalf of the Authors (19 May 2020)  Author's response   Manuscript 
ED: Referee Nomination & Report Request started (11 Jun 2020) by Giuliano Di Baldassarre
RR by Anonymous Referee #2 (12 Jun 2020)
RR by Anonymous Referee #1 (17 Jul 2020)
ED: Publish subject to minor revisions (review by editor) (03 Aug 2020) by Giuliano Di Baldassarre
AR by Yohei Sawada on behalf of the Authors (07 Aug 2020)  Author's response   Manuscript 
ED: Publish subject to technical corrections (14 Aug 2020) by Giuliano Di Baldassarre
AR by Yohei Sawada on behalf of the Authors (17 Aug 2020)  Manuscript 
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Short summary
In socio-hydrology, human–water interactions are investigated. Researchers have two major methodologies in socio-hydrology, namely mathematical modeling and empirical data analysis. Here we propose a new method for bringing the synergic effect of models and data to socio-hydrology. We apply sequential data assimilation, which has been widely used in geoscience, to a flood risk model to analyze the human–flood interactions by model–data integration.