Reduction of vegetation-accessible water storage capacity after deforestation affects catchment travel time distributions and increases young water fractions in a headwater catchment

Hrachowitz, Markus; Stockinger, Michael; Coenders-Gerrits, Miriam; van der Ent, Ruud; Bogena, Heye; Lücke, Andreas; Stumpp, Christine

doi:https://doi.org/10.5194/hess-25-4887-2021

Articles | Volume 25, issue 9

https://doi.org/10.5194/hess-25-4887-2021

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/hess-25-4887-2021

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 25, issue 9

Research article

|

07 Sep 2021

Research article |

| 07 Sep 2021

Reduction of vegetation-accessible water storage capacity after deforestation affects catchment travel time distributions and increases young water fractions in a headwater catchment

Markus Hrachowitz, Michael Stockinger, Miriam Coenders-Gerrits, Ruud van der Ent, Heye Bogena, Andreas Lücke, and Christine Stumpp

Download

Final revised paper (published on 07 Sep 2021)
Preprint (discussion started on 22 Jun 2020)

Interactive discussion

Status: closed

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

- Printer-friendly version

- Supplement

RC1: 'Review', Anonymous Referee #1, 08 Jul 2020
- AC1: 'Replies to Reviewer #1', Markus Hrachowitz, 08 Oct 2020
RC2: 'review hess-2020-293', Anonymous Referee #2, 20 Jul 2020
- AC2: 'Replies to Reviewer #2', Markus Hrachowitz, 08 Oct 2020
RC3: 'Review', Anonymous Referee #3, 29 Jul 2020
- AC3: 'Replies to Reviewer #3', Markus Hrachowitz, 08 Oct 2020
RC4: 'Review of hess-2020-293', Anonymous Referee #4, 14 Aug 2020
- AC4: 'Replies to Reviewer #4', Markus Hrachowitz, 08 Oct 2020

Peer-review completion

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

ED: Reconsider after major revisions (further review by editor and referees) (22 Nov 2020) by Markus Weiler

AR by Markus Hrachowitz on behalf of the Authors (23 Nov 2020) Author's response Manuscript

ED: Referee Nomination & Report Request started (23 Nov 2020) by Markus Weiler

RR by Anonymous Referee #1 (01 Jan 2021)

RR by Anonymous Referee #2 (04 Jan 2021)

RR by Anonymous Referee #3 (10 Jan 2021)

Suggestions for revision or reasons for rejection

Overall the authors did a good job in revising the manuscript. The rebuttal reads a bit strange as it often says that something will be changed, but I assume this is just the text from the discussion phase and things actually have been changed by now. The manuscript has clearly improved by the revision, however, I have still a few points that should be considered:

I appreciate the clarifications regarding the representation of interception. The authors argue that forest removal affects transpiration more than interception. While this obviously is case-specific I would, in general, maintain that the changed interception is the more obvious and often also more important change. While decreased transpiration will be partly compensated for by increased soil evaporation, interception is more of a ‘completely lost process’.

I am not fully satisfied with the responses regarding passive water storage. Yes, water below the wilting point cannot be extracted by the plants, but for most of that water, it can be assumed that some mixing/exchange occurs with more mobile water. I am still wondering what it means if this is not represented in the modelling.

Looking closer at the model performance with respect to the isotope data (Fig 3), I am wondering whether the model really can be said to represent these data. The authors also discuss this issue and report some rather low model performance values. Modelling isotopes is hard, so I don’t want to blame the authors here, but as the novelty of this study is the inclusion of isotope data in the modelling, I am a bit puzzled by these poor model fits. Does this mean that the value of the isotope data is rather limited after all? (assuming that if the fit is poor for the best parameterization, this criterion might not be that helpful in distinguishing between good and not so good parameter sets.

Term effective precipitation: the authors use this term not in its usual way. Usually, effective precipitation is the part of precipitation that makes it to groundwater (=recharge), e.g., http://www.fao.org/3/s2022e/s2022e03.htm. Here it is the precipitation minus interception (but not minus other evaporative fluxes!). I would recommend avoiding this term totally to prevent confusion.

Monte Carlo runs: while 10e6 sounds like a lot, with 14 parameters this means just about 2.7 values along each (parameter)dimensions, i.e., the parameter spaces is sampled rather scarcely. This is an issue of many MC studies, but these days, much larger numbers of runs should be possible, why only one million? This was the standard years ago. Today more runs should be doable, any reason for using one million?

Personally, I would prefer if results and discussion could be separated, this could help to make the manuscript more readable

Eq 42 looks fancy, but I find this a bit confusing, there is only one measure related to O-18, or?

Hide

ED: Reconsider after major revisions (further review by editor and referees) (16 Jan 2021) by Markus Weiler

Dear authors,
the reviewers clearly indicated a considerable improvement of the paper, however, one reviewer still has several points that should be addressed and looking at these points, I can only support the assessment of the reviewer. Hence, I would propose that the authors should careful examine the points and they can hopefully improve the paper regarding these observations. Personally, I am also not happy, that the authors did not consider to use additional data collected in the Wüstebach catchment - certainly, there are only point data, but there is a wealth of point data and there has been many studies showing how to use such a wealth of data to improve the models. Uncertainty should not be an issue as discharge and isotope data as well as the forcing data are also uncertain which is not considered explicitly in the model either.
Looking at the points of reviewer #1, I see in particular

- Interception - many studies show that interception in forest can make up easily 30% of actual ET, so why not considering this process explicitly and limiting I_Max after removing of the forest. I do not understand how Si(t) would be different after the forest removal when I_max is constant.

- Model performance with respect to isotope data: Does this mean that the value of the isotope data is rather limited after all? (assuming that if the fit is poor for the best parameterization, this criterion might not be that helpful in distinguishing between good and not so good parameter sets.

- Monte Carlo runs:

- and due to the lengthy combined result and discussion section, I would also support that the results and discussion should be separated.

I hope that the authors can address these points before I can reconsider the paper for publication in HESS. I would also like to ask the authors to provide a manuscript with track changes, so it is easier for me and the reviewer to follow the changes between the manuscript.

Best regards
Markus Weiler

Hide

AR by Markus Hrachowitz on behalf of the Authors (25 May 2021) Author's response Author's tracked changes Manuscript

ED: Referee Nomination & Report Request started (23 Jun 2021) by Markus Weiler

RR by Anonymous Referee #3 (10 Jul 2021)

ED: Publish as is (19 Jul 2021) by Markus Weiler

AR by Markus Hrachowitz on behalf of the Authors (22 Jul 2021) Manuscript

Short summary

Deforestation affects how catchments store and release water. Here we found that deforestation in the study catchment led to a 20 % increase in mean runoff, while reducing the vegetation-accessible water storage from about 258 to 101 mm. As a consequence, fractions of young water in the stream increased by up to 25 % during wet periods. This implies that water and solutes are more rapidly routed to the stream, which can, after contamination, lead to increased contaminant peak concentrations.