Regionalization with hierarchical hydrologic similarity  and ex situ data in the context of groundwater recharge  estimation at ungauged watersheds

Chang, Ching-Fu; Rubin, Yoram

doi:https://doi.org/10.5194/hess-23-2417-2019

Articles | Volume 23, issue 5

https://doi.org/10.5194/hess-23-2417-2019

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

https://doi.org/10.5194/hess-23-2417-2019

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

Articles | Volume 23, issue 5

Research article

|

17 May 2019

Research article |

| 17 May 2019

Regionalization with hierarchical hydrologic similarity and ex situ data in the context of groundwater recharge estimation at ungauged watersheds

Ching-Fu Chang and Yoram Rubin

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Final revised paper (published on 17 May 2019)
Preprint (discussion started on 07 Jan 2019)

Interactive discussion

Status: closed

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

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RC1: 'Excellent work, but .. what about transferability?', Anonymous Referee #1, 07 Feb 2019
- AC1: 'Response to comments by Anonymous Referee #1', Ching-Fu Chang, 02 Mar 2019
RC2: 'Regionalizing recharge using Hierarchical Hydrologic Similarity-review', Anonymous Referee #2, 09 Feb 2019
- AC2: 'Response to comments by Anonymous Referee #2', Ching-Fu Chang, 02 Mar 2019
RC3: 'Same referee as RC2"', Anonymous Referee #2, 14 Feb 2019
- AC3: 'Response to the extended comment by Anonymous Referee #2', Ching-Fu Chang, 02 Mar 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) (10 Mar 2019) by Mauro Giudici

AR by Ching-Fu Chang on behalf of the Authors (13 Mar 2019) Author's response Manuscript

ED: Referee Nomination & Report Request started (17 Mar 2019) by Mauro Giudici

RR by Anonymous Referee #2 (05 Apr 2019)

Suggestions for revision or reasons for rejection

1. Recommend changing manuscript title

Should change to,
“Regionalization with hierarchical hydrologic similarity and ex-situ data in the context of groundwater recharge estimation at ungauged watersheds”
In the context of – would help emphasize that the method could also be applied to many other processes or study subjects.
groundwater recharge - You estimate LNR not mean annual groundwater recharge

2. Replace mean annual groundwater recharge with a “recharge signature which will be introduced in section ?” or something similar.

Page 4, Line 30 (Introduction): You say you estimate mean annual groundwater recharge but you estimate LNR.

3. Change thresholds for colours in colourbar of figure 3.

Maps don’t show that much spatial variability in recharge, which could be highlighted more if change thresholds.
Also, would be more intuitive if colours got darker with increasing recharge rates.

4. Write section not sect.

Page 17, Line 9
Page 20, Results, Line 5.
Page 21, Line 18

5. Need clearer splitting criteria labels in Figure 9 or explain/describe splitting criteria showing in your trees in a legend.

Page 25: labels such as PPT02, SLP_deg won’t be understood easily by readers who aren’t thoroughly reading the paper and with BGEOL_147 or NLCD01 readers will likely not understand it.

6. Highlight how future users of this method or other data mining methods should be selective about which characteristics they use.

Page 26, Lines 11-14: You make a very nice point about how one variable organic matter content may hold much of the same information as AWC. This can sometimes lead to variables competing against each other as to which one is more important, but in reality they are likely describing the same thing. Therefore, should probably just use the variable which identifies the processes you are interested in the best.
Similarly, sand and clay fractions are likely to be highly negatively correlated, so could use the ratio of sand to clay instead of separate sand and clay fractions. I’m not suggesting this for this paper as your main message is the methodology. However, I think it is important that any future users of the methodology be warned against an approach of chucking all the available information into a machine learning method and just watching what comes out. We should be more thoughtful as to which variables may be important for the processes we are interested in.
Below are some media articles highlighting some of the opinions of a researcher at Rice university in Houston about using machine learning in science.
https://www.eurekalert.org/pub_releases/2019-02/ru-cwt021119.php
https://www.bbc.co.uk/news/science-environment-47267081

6. Sentence needs rephrasing

Page 28, Lines 17-18: “difficult to make physical interpretation our of the results in figure 10” – sounds a bit strange.
Page 33, bottom line: “In a difference case” – should be in a different case.

7. Should have sub-sections for each of the limitations mentioned in section 5.3 and they should appear in the same order they are written in the text.

Page 30, Lines 21-22: state three limitations, but only have sub-sections 5.3.1 and 5.3.2

8. Sub-section numbering need correcting
Currently have,
5.3.1 The scale of target response.
5.3.1 The MRB-based… (should be 5.3.2)
5.0.1 Limited temporal data coverage (should this be 5.3.3 or 5.4)
5.0.2 Non-comprehensive list… (should this be 5.3.4 or 5.4 or 5.5)

9. The storyline is now much clearer and it is easier to follow your key messages and contributions.

Additions to the introduction and discussion have really helped in making a clear story and ensure your main messages are understood by the reader.
The methodology and case study sections are now much easier to follow and I like the examples you give to explain some of your terminology (P11, lines 16-22).

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RR by Anonymous Referee #1 (18 Apr 2019)

ED: Publish subject to technical corrections (23 Apr 2019) by Mauro Giudici

Short summary

Estimates of hydrologic responses at ungauged watersheds can be conditioned on information transferred from other gauged watersheds. This paper presents an approach to consider the variable controls on information transfer among watersheds under different conditions while at the same time featuring uncertainty representation in both the model structure and the model parameters.