The multiscale routing model mRM v1.0: simple river routing at resolutions from 1 to 50&thinsp;km

Thober, Stephan; Cuntz, Matthias; Kelbling, Matthias; Kumar, Rohini; Mai, Juliane; Samaniego, Luis

doi:https://doi.org/10.5194/gmd-12-2501-2019

Articles | Volume 12, issue 6

https://doi.org/10.5194/gmd-12-2501-2019

© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/gmd-12-2501-2019

© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 12, issue 6

Model description paper

|

28 Jun 2019

Model description paper |

| 28 Jun 2019

The multiscale routing model mRM v1.0: simple river routing at resolutions from 1 to 50 km

Stephan Thober, Matthias Cuntz, Matthias Kelbling, Rohini Kumar, Juliane Mai, and Luis Samaniego

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Final revised paper (published on 28 Jun 2019)
Preprint (discussion started on 04 Feb 2019)

Interactive discussion

Status: closed

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

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- Supplement

RC1: 'reviewer report', Anonymous Referee #1, 13 Feb 2019
- SC1: 'Reply to reviewer report by reviewer #1', Stephan Thober, 25 Mar 2019
RC2: 'Reviewer report', Thomas Riddick, 11 Mar 2019
- SC2: 'Reply to reviewer report by Thomas Riddick', Stephan Thober, 25 Mar 2019
AC1: 'A revision following the comments by the reviewers', Stephan Thober, 06 May 2019

Peer-review completion

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

AR by Stephan Thober on behalf of the Authors (06 May 2019) Author's response Manuscript

ED: Publish as is (23 May 2019) by Jeffrey Neal

Short summary

We present a model that aggregates simulated runoff along a river (i.e. a routing model). The unique feature of the model is that it can be run at multiple resolutions without any modifications to the input data. The model internally (dis-)aggregates all input data to the resolution given by the user. The model performance does not depend on the chosen resolution. This allows efficient model calibration at coarse resolution and subsequent model application at fine resolution.