Characterization of soil moisture response patterns and hillslope hydrological processes through a self-organizing map

Lee, Eunhyung; Kim, Sanghyun

doi:https://doi.org/10.5194/hess-25-5733-2021

Articles | Volume 25, issue 11

https://doi.org/10.5194/hess-25-5733-2021

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

https://doi.org/10.5194/hess-25-5733-2021

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

Articles | Volume 25, issue 11

Research article

|

08 Nov 2021

Research article |

| 08 Nov 2021

Characterization of soil moisture response patterns and hillslope hydrological processes through a self-organizing map

Eunhyung Lee and Sanghyun Kim

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Final revised paper (published on 08 Nov 2021)
Supplement to the final revised paper
Preprint (discussion started on 13 Apr 2021)
Supplement to the preprint

Interactive discussion

Status: closed

RC1:
'Comment on hess-2021-107', Uwe Ehret, 17 May 2021

Dear Editor, dear Authors,

Please see my comments in the attachment.

Yours sincerely, Uwe Ehret

Citation: https://doi.org/10.5194/hess-2021-107-RC1
- AC1: 'Reply on RC1', SangHyun Kim, 20 May 2021
  
  Dear Editor
  Thank you very much for your review and comments.
  We revised paper addressing two comments as follows;
  Figure 7 is mentioned in text as;
  Line 411-412: The hydrologic events classified by the SOM can be characterized through comparative feature presentation for all clusters (Figure 7).
  The exemplary events were added in Appendix and referred in text as
  Line 369-370: Appendix presents exemplary events with rainfall and soil moisture responses in upslope and downslope for Clusters 1 to 5.
  
  Appendix section (Line 518-533) is added to represent exemplary events.
  Thanks for your arrangement in advances,
  
  Sanghyun Kim, Ph.D., Prof.
  Dept. of Environmental Engineering
  College of Engineering
  Pusan National University
  Busan, South Korea 46241
  kimsangh@pusan.ac.kr
  
  Citation: https://doi.org/10.5194/hess-2021-107-AC1
RC2:
'Review of “Characterization of Hillslope Hydrologic Events Through a Self-Organizing Map” by Lee and Kim', Anonymous Referee #2, 21 May 2021
Review of “Characterization of Hillslope Hydrologic Events Through a Self-Organizing Map” by Lee and Kim

I found the manuscript very interesting, however, I would say the manuscript needs significant improvement to get to the publication level and some major changes or clarification should be done. My major comments:

The manuscript is written with a simple language however it is still very difficult to easily follow the manuscript. I think, although, the use of the English language in formulating the sentences is sufficient however the logical flow of the text is not intuitive and hampers by evolving around the technicalities and repetition.

I think figures can be improved and can be better explained in the text. For example, it is very hard for me to comprehend Figure 2 (and other figures which perhaps has a lot of dense information).

Can the authors perhaps provide a more physical understanding of the clusters?

I think the questions which the authors are asking were not directly answered. Perhaps the questions can be better elaborated in the discussions and reflect on the conclusions.

The key points are very vague please make them more specific to this study and the finding of this study. Title can also be improved; title is very generic and broad.

Perhaps reduce the long explanation on the method and wordy results to sharpen the messages.

I would like to encourage the authors to bring their study into wider hydrological modeling efforts. What is the message of the results for the hillslope hydrology at a larger scale? The hydrological models carry memory (antecedent soil moisture) for example, so the strong correlation the author is showing here is implicitly taken care of in the models that using time-stepping of storage over time. I do not see an important message from this study which is different from the general knowledge that we already have on how hillslope might behave; the findings may not be that different from what it can be inferred from a model. as an example, how Figure 4 would look like if the authors have repeated their study on a hydrological model at hillslope scale rather than the data itself. I would say we would strongly find the same pattern, so what is new? The authors can cite modeling work at catchment scale and try to contextualize their work. The previous studies such as Fang, Clark, et al., 2019 WRR, Loritz et al., 2017 HESS, Gharari et al., 2014 HESS, Gharari et al., 2011 HESS, Gao et al., 2014 HESS among others.

I believe the manuscript needs to be significantly improved on multiple fronts. Readability and consistency of the flow of the manuscript, clarity of the messages that can be used in a broader context which can provide us with better ability to understand the system and hence improve the models at hillslope. I believe major revision is inevitable.

With kind regards,
Citation: https://doi.org/10.5194/hess-2021-107-RC2
- AC2: 'Reply on RC2', SangHyun Kim, 24 Jun 2021
  
  Thanks for your constructive comments.
  Please find responses for your comments in enclosed file namely "Response to comments for Reviewer 2.pdf".
  Thanks
  
  Citation: https://doi.org/10.5194/hess-2021-107-AC2

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload

ED: Reconsider after major revisions (further review by editor and referees) (07 Jul 2021) by Erwin Zehe

Dear Lee,

I read your paper with great interest and agree with both reviewers that this work has great potential to evaluate to which extend machine learning methods can help to classify soil moisture events and to search for underlying reasons. Yet, I think in line with the assessment of reviewer 2 that the manuscript needs major revisions to fully explore it’s potential. In addition to the points raised by the reviewer, I I’d like to bring the following points to your attention.

Figure 2 is indeed difficult to digest. Maybe it is better to present boxplots not using the profile names but their topographical elevation on the x-axis (more information), and it might be better to separate different depths into different panels.

I have furthermore problems with the definition of the maximum soil moisture variation VAR. A normalization with the antecedent soil moisture is hydrologically misleading. Let me explain this based on two cases:
1) Theta_max = 0.4, Theta_asm =0.3 gives a var of 33%,
2) Theta_max = 0.15, Theta_as = 0.05 gives a var of 200%,

In fact in the first case the storage change was 200% larger than in the second. I think a normalization with total precipitation depth is hydrologically much more appropriate. You could calculate storage changes, for instance by multiplying changes in theta with the respective depth increments that are represented by these measurements. VAR will then compare normalized storage changes, and the normalization is constant and not variable due to the variability of ASM between the profiles (see Fig. 3). To me this is a hydrologically much more meaningful index, which relates storage changes to the total forcing.

Related to this, I think that Fig. 3b is misleading, as the variations downslope are normalized with systematically elevated antecedent soil moistures. The proposed normalization with total precipitation will rectify this and the downslope var will become likely larger than the upslope var. And it might change the results of the clustering and will differences more meaningful.

Figure 4 is interesting, but the numbers are too small. Please clarify whether this is the coefficient of determination R2 or the correlation R. The corresponding text mentions both. I also wonder whether you could correlate ASM and optional other predictors with VAR (to explain variations between the profiles).

Last but not least, I agree with reviewer 2 that a clear physical interpretation of the clusters is highly desirable. Boxplots are an abstract representation of an event. In a different context (model error classification), Reusser et al. (2009) used typical errors in runoff events and classified those with am SOM. I am sorry to mention my own work in this context, this approach helped to interpret the corresponding error clusters (and to create an imagination how they looks like). Another option would be to show the events closed to the cluster centroids.

Best regards,

Erwin Zehe

References:
Reusser, D. E., Blume, T., Schaefli, B., and Zehe, E.: Analysing the temporal dynamics of model performance for hydrological models, Hydrology And Earth System Sciences, 13, 999-1018, 2009.

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AR by SangHyun Kim on behalf of the Authors (10 Aug 2021) Author's response Author's tracked changes Manuscript

ED: Referee Nomination & Report Request started (12 Aug 2021) by Erwin Zehe

RR by Uwe Ehret (16 Aug 2021)

RR by Anonymous Referee #2 (26 Sep 2021)

ED: Publish as is (29 Sep 2021) by Erwin Zehe

AR by SangHyun Kim on behalf of the Authors (07 Oct 2021)

Short summary

In order to understand hillslope hydrological processes during rainfall runoff events, rainfall characteristics and responses of soil moisture at the hillslope scale were explored by applying self-organizing map (SOMs) to a dataset. Combinations of upslope and downslope spatial patterns of hillslope hydrological processes, vertical flow, and lateral flow along surface or subsurface boundaries were responsible for the distinctions between the event clusters.