Articles | Volume 20, issue 5
Research article
30 May 2016
Research article |  | 30 May 2016

Data assimilation in integrated hydrological modelling in the presence of observation bias

Jørn Rasmussen, Henrik Madsen, Karsten Høgh Jensen, and Jens Christian Refsgaard


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 (07 Dec 2015) by Insa Neuweiler
AR by Jørn Rasmussen on behalf of the Authors (17 Jan 2016)  Author's response    Manuscript
ED: Reconsider after major revisions (24 Jan 2016) by Insa Neuweiler
ED: Referee Nomination & Report Request started (08 Feb 2016) by Insa Neuweiler
RR by Anonymous Referee #1 (12 Feb 2016)
RR by Anonymous Referee #3 (07 Mar 2016)
ED: Publish as is (15 Mar 2016) by Insa Neuweiler
Short summary
In the paper, observations are assimilated into a hydrological model in order to improve the model performance. Two methods for detecting and correcting systematic errors (bias) in groundwater head observations are used leading to improved results compared to standard assimilation methods which ignores any bias. This is demonstrated using both synthetic (user generated) observations and real-world observations.