Insights into the water mean transit time in a high-elevation tropical
ecosystem

Mosquera, Giovanny M.; Segura, Catalina; Vaché, Kellie B.; Windhorst, David; Breuer, Lutz; Crespo, Patricio

doi:https://doi.org/10.5194/hess-20-2987-2016

Articles | Volume 20, issue 7

https://doi.org/10.5194/hess-20-2987-2016

© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

https://doi.org/10.5194/hess-20-2987-2016

© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 20, issue 7

Research article

|

26 Jul 2016

Research article |

| 26 Jul 2016

Insights into the water mean transit time in a high-elevation tropical ecosystem

Giovanny M. Mosquera, Catalina Segura, Kellie B. Vaché, David Windhorst, Lutz Breuer, and Patricio Crespo

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Final revised paper (published on 26 Jul 2016)
Preprint (discussion started on 18 Jan 2016)

Interactive discussion

Status: closed

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

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RC1: 'review HESS 2015-46', Anonymous Referee #1, 19 Feb 2016
- RC2: 'Review Mosquera et al., HESSD', Christian Birkel, 27 Feb 2016
  - AC2: 'Reply to Christian Birkel', Giovanny Mosquera, 29 Mar 2016
- AC1: 'Reply to Referee 1', Giovanny Mosquera, 29 Mar 2016

Peer-review completion

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

ED: Reconsider after major revisions (01 Apr 2016) by Christine Stumpp

AR by Giovanny Mosquera on behalf of the Authors (11 May 2016) Author's response Manuscript

ED: Referee Nomination & Report Request started (13 May 2016) by Christine Stumpp

RR by Christian Birkel (22 May 2016)

RR by Anonymous Referee #1 (09 Jun 2016)

Suggestions for revision or reasons for rejection

GENERAL COMMENTS

I appreciate the authors’ kind and detailed replies and I think the paper is now improved. Still, there are in my opinion some misunderstandings on the concept of Mean Transit Time (MTT) that I will try to explain with more detail. I think the authors had a good point in limiting the analysis to baseflow conditions, but some more efforts could be put to clarify the meaning of their analyses.

-The MTT is the mean of a distribution and as such it has some very useful mathematical properties. When the distributions are skewed, the mean is strongly affected by the “heaviness” of the tail, which is typically quite pronounced in catchments [see Kirchner, 2000]. The tail of the distribution is very difficult to estimate, especially in systems where the output signal is not very informative. This can be because the output is very damped with respect to the input, or because the input is characterized by regular fluctuations around a constant trend. Both of these are typical situations with water stable isotopes. In these cases, one may well be able to describe the measured solute response with a number of different functions which have the same ‘young’ component but very different ‘old’ components (or tails). Unfortunately, this has a huge impact on the mean of the distribution, which then remains very uncertain. Some authors have started to describe other properties of the transit time distributions (TTDs) other than the mean, like the median transit time [e.g. Soulsby et al., 2015], or the “young water fraction” [e.g. Kirchner et al., 2016ab].

-Given the point above, it is clear that estimating catchment TTDs is not a trivial task, and uncertainty is often inevitable. For this reason, I am a bit skeptical about the fact that the exponential distribution is the most appropriate to describe the pàramo catchments. In my opinion, such a distribution is better identified because it has not enough degrees of freedom and the same distribution is used to fit short-term and long-term output features. As the short-term features are the only one providing information, they dominate the identification of the function. However, I would argue this is an “apparent” identification because it explains stream chemistry fairly well and parsimoniously, but is not able to reliably estimate the older water components, which have a large impact on the MTT. Other functions tested by the authors are less determined, in my opinion, because they allow a de-coupling between short-term and long-term information. Indeed, both the GM and TPLR predict MTT which are less constrained (296-1478 days and 356-1738) but also much larger than the EP (166-224 days). Doesn’t this suggest that there may be a larger old water contribution than the one predicted by the EP? To further explore this problem it may be interesting to compare the results in terms of other metrics (e.g. are the median or the young water fraction similar in the EP and GM models?).

-Finally, the idea that one single TTD exists is misleading. Any natural hydrologic domain responds differently before, during and after being forced by a storm event. This is not just about seasonality, it’s also about each storm that crosses the catchment after the considered precipitation event and makes transit time distributions intrinsically non-smooth curves. Moreover, stream concentration is affected by the specific hydrologic conditions that take place at the time of sampling, and not by the average catchment conditions. This of course does not mean that stationary analyses are meaningless, but it should be clear that they try to depict an average catchment condition, which is often very different from any actual situation.

Overall, I don’t want to look too critical about this work, but I think the paper would benefit from acknowledging a more realistic view on transit time distributions.

Other general comments are:
-as the AIC criterion was introduced, which takes into account the number of parameters, I think the Measure of Identification (MI) could be removed from the analysis, as it is redundant and applied rather arbitrarily given the lack of prior knowledge on the parameters.
-I think it may be worth reducing the discussion section, which is currently very long and include the repetition of concepts which were already mentioned in the results.

DETAILED COMMENTS
Abstract: it may be worth to specify from the beginning that the MTT refers to baseflow conditions
Page 4, line 7: please specify that you mean MTT variability among catchments
P. 4, l. 23: the first source of non-stationarity which should be mentioned is precipitation variability
P. 4, l. 27: what do you mean by stating that the cited works “have yielded results with high degree of uncertainty”? I personally think those works just show the complexity of the problem in more realistic terms.
P.5, l.3: what is a mathematical limitation?
P.9, l.19: I think this is a good point to mention that, as you do a steady-state analysis, you limit your study to the transit times of baseflow.
P.11, l.15: I think this is a too strong sentence, which needs more context.
P.12, l.14: as mentioned in the general comments, I don’t think the MI is necessary anymore.
P. 12, l.25-27: first you say that total runoff is “spatially more heterogeneous”, but then you say that Runoff coefficients show “relatively low spatial variability”. This sounds inconsistent.
P.14, l.16: I think the threshold on the KGE is critical for the parameter uncertainty. Could the author observe important differences with a different values? I am also wondering whether the models with a higher number of parameters would require a higher threshold.
P.14, l.21 (Figure 3): I thinks there is no need to show the isotopic content of precipitation in this figure, as it was already presented in figure 2b. Moreover, such broad Y-axis makes it difficult to assess modeled and measured 18O in streamflow. I think the authors could reduce the Y-axis to e.g. [-8, -14]. Please also avoid the use of biweeks at the x-axis.
P.15, l.9-10: “rather than from a more realistic representation of the hydrologic functioning of the catchments”. This is a very strong and not justified statement.
P. 16, l. 20-24: I had already commented on this, but I see that we probably did not understand each others. First, the unit “biweeks” is rather unusual and I recommend using days (or months, or years) instead. As the exponential function integrates to 1 only in the limit to infinity, the notion of “completely recovered” is linked to a threshold (e.g. 99%) and I suggest to mention it. Finally, I don’t fully agree with the last sentence. Even in a 3 years dataset, the first months are strongly affected by hydrologic events that had happened before the beginning of the measurements.

ADDITIONAL LITERATURE
Kirchner, J., Feng, X., & Neal, C. (2000). Fractal stream chemistry and its implications for contaminant transport in catchments. Nature, 403(6769), 524–7. http://doi.org/10.1038/35000537

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ED: Publish subject to minor revisions (Editor review) (10 Jun 2016) by Christine Stumpp

AR by Giovanny Mosquera on behalf of the Authors (20 Jun 2016) Author's response Manuscript

ED: Publish as is (27 Jun 2016) by Christine Stumpp

AR by Giovanny Mosquera on behalf of the Authors (28 Jun 2016)

Short summary

This study focuses on the investigation of baseflow mean transit times (MTTs) in a high-elevation tropical ecosystem (páramo) using stable water isotopes. Results showed short MTTs (< 9 months) and topographic controls on their spatial variability. We conclude that (1) the hydrology of the ecosystem is dominated by shallow subsurface flow and (2) the interplay between the high storage capacity of the páramo soils and the catchments' slopes provides the ecosystem with high regulation capacity.