Unravelling abiotic and biotic controls on the seasonal water balance using data-driven dimensionless diagnostics

Seibert, Simon Paul; Jackisch, Conrad; Ehret, Uwe; Pfister, Laurent; Zehe, Erwin

doi:https://doi.org/10.5194/hess-21-2817-2017

Articles | Volume 21, issue 6

https://doi.org/10.5194/hess-21-2817-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

https://doi.org/10.5194/hess-21-2817-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 21, issue 6

Research article

|

09 Jun 2017

Research article |

| 09 Jun 2017

Unravelling abiotic and biotic controls on the seasonal water balance using data-driven dimensionless diagnostics

Simon Paul Seibert, Conrad Jackisch, Uwe Ehret, Laurent Pfister, and Erwin Zehe

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Final revised paper (published on 09 Jun 2017)
Preprint (discussion started on 09 Mar 2016)

Interactive discussion

Status: closed

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

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- Supplement

RC1: 'Review', Anonymous Referee #1, 16 Mar 2016
- AC1: 'reply to the review posted by the Anonymous Referee #1 on 16 Mar 2016', Simon Seibert, 23 Mar 2016
RC2: 'Review comment', Anonymous Referee #2, 12 Apr 2016
RC3: 'Review', Anonymous Referee #3, 16 Apr 2016
EC1: 'Editor comment', Fabrizio Fenicia, 18 May 2016
- AC2: 'Final response', Simon Seibert, 01 Jul 2016

Peer-review completion

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

ED: Reconsider after major revisions (18 May 2016) by Fabrizio Fenicia

AR by Simon Seibert on behalf of the Authors (22 Dec 2016) Manuscript

ED: Referee Nomination & Report Request started (06 Jan 2017) by Fabrizio Fenicia

RR by Anonymous Referee #3 (01 Feb 2017)

Suggestions for revision or reasons for rejection

The text is significantly revised (and shortened!), and the story is much clearer in this recent draft. However, there are points that could be improved upon through minor revision of the text and some tempering of conclusions drawn. One of my main major criticisms is that there is a lot described in the text in terms of comparisons ACROSS sites, but no cross-site figures. The authors may wish to consider removing Figure 7 and replacing with a cross-site comparison figure that highlights the differences between type I and type II curve indices, and to frame this in the context of the interpretation presented in the discussion.

Major comments:
-A significant portion of your results is the discussion of your regression between catchment characteristics and dDMC characteristics. Unless I missed it, I did not see any mention of thresholds for significance or inclusion/exclusion of important variables within the multiple regression. We know that many hydrological relationships are nonlinear, and so merely testing using a linear correlation coefficient could neglect other important relationships that may exist.
-Are you suggesting that metrics related to dDMC be used in addition to SFDC, or are a better approach than SFDC to characterize rainfall-runoff relationships?
-I am not convinced that an r2 of 0.22 indicates that two variables interact to influence tau (pg 14 lines 5 – 15). An r2 of 0.22 is still a very poor value. I would consider tempering some of the statements made about relationships between landscape characteristics and response variables. Again, are these relationships statistically significant? If anything, these results indicate that there are probably more disparate controls related to landscape variables not included here or competing effects between landscape variables and climate that mediate many of these relationships.
-There were many grammatical issues and missing words throughout. I suggest the authors give the manuscript a careful and thorough read.
- Your scope neglects your comparison to SFDCs, which I see as a potential contribution to the manuscript, given how much you have highlighted it. Consider restructuring these questions to include reference to SFDC.
-Figure 7: I find it difficult to connect the point you are trying to make with this figure, and I am not sure it is needed. What would be more useful would be to see comparison of type I and type II curve outputs, and how these could be interpreted to provide different information across your study catchments to augment the discussion on pages 17 and 18.

Minor comments:
Pg 1 line 3: confusingly written
Pg 1 line 8: grammar
Pg 1 lines 16 – 18: vegetation vs. winter period – perhaps there are more scientific options for these terms? Growing season?
Pg 2 line 3: incorrect citing
Pg 4 lines 9 through 30 I found to be confusing. The postulating, followed by Q1, make it difficult for the reader to follow your logic without having already read the paper. After reading the paper, I understand the points you are trying to make, but I found a lot of this to be almost wishy-washy. If it were interspersed with each of the questions to perhaps motivate these different investigations (and why you are doing them), I think the reader might draw more from what you have written.
Pg 11 Line 6: reference to incorrect section?
Pg 13 line 26 Reference tables here? There were more than 24 characteristics in Table 2 and 3 – it’s worth noting which were included in the regression analysis

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RR by Anonymous Referee #2 (08 Feb 2017)

ED: Publish subject to revisions (further review by Editor and Referees) (23 Feb 2017) by Fabrizio Fenicia

AR by Simon Seibert on behalf of the Authors (03 Apr 2017) Author's response Manuscript

ED: Publish as is (09 Apr 2017) by Fabrizio Fenicia

AR by Simon Seibert on behalf of the Authors (26 Apr 2017)

Short summary

Runoff production mechanisms and their corresponding physiographic controls continue to pose major research challenges in catchment hydrology. We propose innovative data-driven diagnostic signatures for overcoming the prevailing status quo in inter-comparison studies. Specifically, we present dimensionless double mass curves which allow us to infer information on runoff generation at the seasonal and annual timescales. The method is based on commonly available data.