the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 08 Oct 2024
Dams extend the surface water renewal time in inland river basins: A comparative study based on stable isotope data from two different basin
Abstract. The dramatic increase in the number of dams on rivers in recent years have led to a more complicated water circulation mechanism in arid regions, Capturing the impact of dams on water circulation processes is an ongoing challenge in the hydrology field. By utilizing observational isotopic data from water bodies, we conducted a comparative study on the Fyw and MTT in two inland river basins within the arid zone of Central Asia. Research findings suggest that dams amplify the damping effect and phase shift of seasonal fluctuations in river water, which in turn extends the water circulation period within inland river basins. The cascading interception of river water by dams has substantially reduced the proportion of young water (Fyw) in the river and has nearly tripled the mean transit time (MTT) of river water. This work confirms the fact that dams are profoundly influencing the water circulation processes in inland river basins from an isotopic kinetic perspective, and is useful for understanding the mechanisms driving water circulation times arid areas.
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RC1: 'Comment on hess-2024-277', Anonymous Referee #1, 19 Nov 2024
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This is potentially an interesting study but, as written, this paper falls short of what is required for publication in a major international journal such as HESS. I have provided several general comments but have not gone through some of the sections (the results or regional setting) in detail as the basis of the paper needs serious attention. In its current form, presenting results with little discussion or explanation (and not outlining what is novel) is unlikely to create interest with a broad international readership. I understand that getting negative results is never pleasant, but I hope that these comments help in revising the study.
Here are the general issues with the paper.
Firstly, there is a general lack of explanation such that the reader cannot easily follow aspects of the text . The paper is relatively short; however, the brevity has been achieved at the expense of clarity and rigor. For example, lines 51-75 present the general the technical background and this section needs to convey to the reader the important background and identify knowledge gaps, problems, or contrasting approaches. However, it falls short of this, for example:
1) L54-58. Some broader discussion of mean transit times and the issues around these would be useful.
2) Likewise, you should define what the young water fraction is and why it is important. The approach of determining Fwy rather than a mean transit time is due to flow systems not being stationary (which is an assumption in much of the early work using tracers such as stable isotopes to determine MTTs). This is well discussed in Kirchner (2016) and Jasechko et al. (2016), both of which you cite.
3) Statements such as: “There are a number of factors influencing the water transit times” (L66) need explaining – what are they and how do they impact MTTs?
4) The Methods (Section 3) are also brief and a bit more detail on lumped parameter models (especially the gamma model, which is the one that you choose) is also needed.
Secondly, the calculations need to be more rigorous and thought through more. The basic outline of the calculations is presented in Section 3.2 and Section 5 presents the calculated results. However, nowhere is there any real discission of the results. Specifically:
5) You choose to estimate MTTs as well as Fwy but part of the reason for using Fwy is due to the stationarity problem that was identified by Kirchner (2016). Briefly that is that the assumption made when using LPMs with seasonal tracers that the flow system does not change over the year such the MTT is constant at all flows. However, the reality is that catchments discharge younger water during wetter conditions and older water during dry periods. Studies using tracers such as tritium (e.g. Cartwright et al., 2020, which you cite) and studies using other techniques such as flux tracking (e.g. Hrachowit et al., 2013. Hydrology and Earth System Sciences, 17, 533–564. https://doi.org/10.5194/hess-17-533-2013) or StorAge solutions (Benettin et al., 2015 Water Resources Research, 51, 9256–9272. https://doi.org/10.1002/2014WR016600) also show this. Given that this issue is implicitly recognised, is it really valid to calculate MTTs using a lumped parameter model?
6) If you do use a lumped parameter model, you need to discuss some of the associated potential problems, such as:
- Aggregation (i.e. macroscopic mixing from different sources); this is discussed in Kirchner (2016, Hydrol. Earth Syst. Sci., 20, 279–297, https://doi.org/10.5194/hess-20-279-2016).
- Truncation, which is the possibility that there is older water with an attenuated signal, such that the MTTs are underestimated (e.g. Stewart, et al., 2010, Hydrol. Process. 24, 1646–1659. https://doi.org/10.1002/hyp.7576). Given the longest MTTs you estimate are >9 years, this is likely to be a significant issue.
7) What are the parameters in the gamma model and why where they chosen? The transit time distributions in this model vary with the alpha parameter (e.g. Stewart et al., 2017. Hydrol. Earth Syst. Sci., 21, 4615–4627, https://doi.org/10.5194/hess-21-4615-2017 ) and the calculated MTT also varies. It looks like you have used only a single parameterisation but there are not details of which one and why it was chosen. Is there any advantage of using the gamma model over say the exponential or exponential-piston flow lumped parameter models or the dispersion model (which like the gamma model is fairly generic)
8) Uncertainties are discussed (Sections 5.1 and 5.3), but it is not always clear what was taken into account. Statements such as “As the spatial and temporal heterogeneity of the basin may cause errors in the MTT estimates, we used Fyw to constrain the estimated MTT results” are not very clear. There are several uncertainties that should be included, such as:
- Uncertainties arising from the derivation of the input function. Figure 3 shows that there is a decent sinusoidal variation in the precipitation isotopes, and that the fitted curve is reasonable but there will still be an uncertainty here that translates into errors in Fyw and MTTs
- The impacts of varying the parameters in the lumped parameter models
- Aggregation and truncation
The papers that you cite plus the ones also referred to here have a far higher lever of rigor than you have attempted and the results come across as being far more convincing.
Finally, I am not convinced about the importance and novelty of the study.
- Concluding that water transit times in dammed catchments are longer would seem unsurprising (the reservoirs behind the dams have a storage time that is longer than the storage time in a free-flowing river after all). So, what is the new understanding here?
- Are there other studies with which you can compare this work (which would place it in a better international context)? If it is the first such study, then discuss that and perhaps do more justification that the calculations can apply to heavily modified rivers that are more susceptible to evaporation which obviously modifies the stable isotopes.
Citation: https://doi.org/10.5194/hess-2024-277-RC1
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