A proposed method for estimating interception  from near-surface soil moisture response

Acharya, Subodh; McLaughlin, Daniel; Kaplan, David; Cohen, Matthew J.

doi:https://doi.org/10.5194/hess-24-1859-2020

Articles | Volume 24, issue 4

https://doi.org/10.5194/hess-24-1859-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/hess-24-1859-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 24, issue 4

Research article

|

15 Apr 2020

Research article |

| 15 Apr 2020

A proposed method for estimating interception from near-surface soil moisture response

Subodh Acharya, Daniel McLaughlin, David Kaplan, and Matthew J. Cohen

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Final revised paper (published on 15 Apr 2020)
Preprint (discussion started on 23 Apr 2019)

Interactive discussion

Status: closed

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

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SC1: 'Previous submission', D. A. Kaplan, 10 May 2019
RC1: 'Interesting analysis, but claim is too strong given the evidence.', Anonymous Referee #1, 18 Jun 2019
- AC1: 'Response to Anonymous Referee #1', Subodh Acharya, 09 Sep 2019
RC2: 'Discussion of HESS-2019-157', John Van Stan, 13 Aug 2019
- AC2: 'Response to Referee #2', Subodh Acharya, 09 Sep 2019

Peer-review completion

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

ED: Reconsider after major revisions (further review by editor and referees) (07 Oct 2019) by Miriam Coenders-Gerrits

As seen in the 2 review reports, both reviewers appreciate your attempt to estimate interception by looking at shallow soil moisture content.However, they also share their concerns on:
1) lack of validation data
2) limited throughfall data (in relation to spatial variability)
3) effect of antecedent soil moisture, lateral flow en preferential flow
Despite the authors extensive reply, I still think their conclusions remain too strong. I do understand that this study was a 'bi-product' and therefore no validation data is available, however this does not justify limited founded conclusions. Therefore, I highly recommend to downtune your conclusions even more, plus I would like to see:

1) What is the effect of the uncertainties in Gash plus Hydrus (separately but also together). Are these uncertainties not larger than the variability in soil moisture?
2) I appreciate your statement on total interception capacity. However, it's not so straightforward to simply add the two. First of their is a cascading effect of the two storages (first the canopy storage has to be fill, before the litter storage will be filled). This causes a time delay. Secondly, the atmospheric demand (± potential evaporation) is different for the canopy than for the litter. This causes a difference in the emptying time (time scale).
3) In your reply about lateral and preferential flow, you only refer to a change in 'arrival time'. However, both also (and maybe more importantly) cause a spatial redistribution. Here again the number of throughfall gauges and soil moisture probes becomes important.
4) Please, carefully check your reference list. Some references are missing and many typos exist.

I am looking forward to you major revised manuscript.

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AR by D. A. Kaplan on behalf of the Authors (15 Nov 2019) Manuscript

ED: Referee Nomination & Report Request started (29 Nov 2019) by Miriam Coenders-Gerrits

RR by Anonymous Referee #1 (01 Jan 2020)

Suggestions for revision or reasons for rejection

The changes in the main text of the manuscript and in the abstract accommodate most of my main concerns (but see below). I would like to emphasize again that I like the idea, I like the data. I would like this research to be published. However, I strongly disagree with some parts of the presentation.

The authors prefer to stick with the original message, which is a choice I still do not support. The authors claim that excellent research during the last decades on that topic (no references given) has already shown what they have shown. I disagree. This is a one of a kind experimental setup investigating for the first time that soil moisture response after rainfall can be explained by vegetation properties. This is a very good study, and a great idea for making this point. In my opinion the authors give the best part of their contribution away for a less interesting and less validated alternative. After the revision I am still not convinced otherwise.

If the authors prefer to stick with the current story, I find that a change of the title is warranted, e.g. by including „a potential method“ . Be creative. But I find it unjust to claim in the title that a method for interception measurement is presented when direct validation was not part of the study. The argument that interception data from similar vegetation are available is circular. This does show that the results are in the ballpark and plausible. I am not doubting this. But in the end the paper compares the derived differences in interception between measurement places, and no data exist to validate those smaller differences. They could alternatively be due to soil properties, and in absence of direct data . Acknowledging this does not take anything away from the study.

Also, the message of some of the cited papers in the new version is somewhat distorted to the point where I find it an unfaithful representation of the original research (see below). This should be repaired.

R1-C7
The response did not address the raised concern. The concern is that given the spatial heterogeneity, the application of the proposed method requires more measurement effort as compared to above ground measurements only. The authors main response is that they do not think it undercuts the utility of their findings - I agree. But it does undercut the claim that the methods is potentially „cost saving and with logistical advantage“ compared to interception measurements as stated in the abstract. This should be addressed.

Unfortunately the references cited in response to my comment are interpreted in a somewhat biased fashion. First, Metzger et al. (2017) show that soil water content increase for the majority of events was not related to soil water content increase. Second, Zimmermann et al. (2014) recommend 5 funnels (of minimum 1 m2 sampling size, e.g. 0.5 m wide and 2 m long) for multiple events. Your method applies to single events, for which they recommend 10 - 20 troughs of substantially larger size than covered by the soil moisture sensors in this study. An interpretation that three samplers are almost sufficient is misleading in context with the presented methods, please change this part of the revised manuscript.

References

Metzger, J.C., Wutzler, T., Dalla Valle, N., Filipzik, J., Grauer, C., Lehmann, R., Roggenbuck,
M., Schelhorn, D., Weckmüller, J., Küsel, K. and Totsche, K.U., 2017. Vegetation impacts soil water content patterns by shaping canopy water fluxes and soil properties. Hydrological processes, 31(22), pp.3783-3795.

Zimmermann, A. and Zimmermann, B.: Requirements for throughfall monitoring: The roles of temporal scale and canopy complexity. Agricultural and forest meteorology, 189, 125-139, 2014

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ED: Reconsider after major revisions (further review by editor and referees) (14 Jan 2020) by Miriam Coenders-Gerrits

AR by D. A. Kaplan on behalf of the Authors (07 Feb 2020) Manuscript

ED: Publish subject to minor revisions (further review by editor) (17 Feb 2020) by Miriam Coenders-Gerrits

AR by D. A. Kaplan on behalf of the Authors (28 Feb 2020) Author's response Manuscript

ED: Publish as is (05 Mar 2020) by Miriam Coenders-Gerrits

AR by D. A. Kaplan on behalf of the Authors (10 Mar 2020) Manuscript

Short summary

Interception is the storage and subsequent evaporation of rain by vegetation and surface litter. Quantifying interception is critical for understanding the water balance, but it can be difficult and costly to measure. We developed an approach to estimate interception using automated soil moisture measurements during rainfall events. Results suggest that interception can be estimated using soil moisture data, leading to potential cost savings and logistical advantages over conventional methods.