the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 06 Nov 2024
Using global reanalysis and rainfall-runoff model to study multi-decadal variability in catchment hydrology at the European scale
Abstract. This study explores the ability of global reanalyses to simulate catchment hydrology at the European scale using a conceptual rainfall–runoff model. We used two reanalyses, NOAA 20CR and ERA-20C, to simulate daily streamflows for over 2000 catchments since the 1840s. Our findings show that both reanalyses perform well, particularly for mean flows, with simulation performance improving as catchment size increases, though challenges remain for Mediterranean and snow-dominated regions. Additionally, the study highlights significant multi-decadal variations in streamflow, revealing alternating wet and dry periods across Europe. These findings provide valuable insights into long-term hydrological trends and offer a useful framework for understanding future changes in both water resources and hydrological extremes, such as floods, under climate variability.
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RC1: 'Comment on hess-2024-336', Anonymous Referee #1, 02 Jan 2025
This paper presents an analysis of the century-long ERA-20C and NOAA-20CR reanalysis products to simulate flows and long-term trends that could otherwise be missed when looking at shorter time periods. I think the study is of interest and proposes an alternative and convincing argument that the streamflows alternate between wet and dry periods over long (i.e. decadal or longer) time periods. While I found the paper to be well written and interesting, I also have some issues that I think would need to be solved before recommending acceptance for publication.
1. The title should reflect the fact that the reanalyses are not just global reanalyses. They are century-long reanalyses, which is the real kicker and novelty.
2. Line 63: Define what the 20CR and 20C mean (20th century reanalysis, please add)
3. Line 64: "eight-times daily" --> Better to say 3-hourly.
4. Line 81: "such modeling" --> such a modelling"
5. I see the resolution is a key issue in this paper. For starters, the MSWEP+ERA5 combination is mismatched, and the authors should have considered ERA5-Land to match the MSWEP precipitation resolution (0.1° each). Furthermore, to preserve coherence, ERA5-Land precipitation could have been used instead of MSWEP. I think a justification of this should be provided as well as an impact analysis (not redoing runs, but perhaps contextualizing with respect to the size of the catchments?).
6. In a similar vein, catchments sizes were restricted to above 100km2, whereas the ERA and NOAA datasets cover swaths of land between 10000 and 17000km2, which is a huge mismatch, especially the strong elevation gradients all over large parts of Europe. Was downscaling not an option? It seems that at least with the altitude/elevation and some background information it would be possible to do at least a rudimentary approach. I think the authors should consider this in their next version, or at least discuss it in more details because it is a key element of the paper.
7. KGE version used is the 2009 version, whereas the community has moved on to the 2012 modified KGE. While I have no problem with this (it is still a good metric), it would be good to explain that this was an editorial choice.
8. Line 198: "manipulated" has a negative connotation. I would suggest: "was implemented".
9. It seems Figure 2a-c first boxplot is not colored in red as supposed to? Or is it some other variable, given there are 9 boxes and only 8 legend entries? Which seems true for the two other boxplots as well. Please clarify.
10. Lines 248 and 256: p-value can be set to 0 when it is basically machine precision (2.2e-16).
11. Figure 5: One problem here is that the top rows will be a significant subset of the bottom rows, so the results are not necessarily comparable. For example, imagine that 50% of the catchments only have validation data on the exact 1982-1995 period. That would mean that those basis' scores would be exactly the same in the bottom plots even though it should cover la longer period, but it cannot be interpreted that way. I would suggest identifying a series of catchments that have at least 50 years of validation data and keeping those independent for the long-duration tests.
12. Lines 275-276: I think this is useful information that should be shown as it would show another mode/dimension to the problem that filters out random perturbations and focuses on the longer-term patterns.
13. General comment: It would be good to have a series of simulations for which only the ones that obtained KGE in calibration/validation above a certain quality threshold are preserved. Ex KGE > 0.7 for NOAA/NOAA and ERA/ERA (not really useful to do ERA5+MESWEP/NOAA(ERA). This would ensure results are not negatively affected by poorly modelled basins/models, as we have some that have quite low KGE values that contribute to the detailed variability results, and are perhaps not as trustworthy.
14. Figure 6: Not clear why the number of catchments changes for each metric. I would assume they would be the same from one metric to the next since they are only excluded if they don't have 30 years of observations?
15. Figure 6: I would show the boxplots in their entirety here. Not much use limiting to 0.2. At least to 0.0.
16. Lines 310-311: There have been numerous studies on this previously, I think it would be good to reference a few to show that your results are in-line with the current literature.
17. Line 321: "of this work" --> "for this work"
18. Lines 334-335: But also human intervention, forestry, agriculture, urbanization over the past ~120 years has definitely had an impact on hydrological response.
19. Figure 11: I think there is a problem here, all three figures are exactly the same.
20. Lines 407-408: But at the same time, the MSWEP + ERA5 dataset would still outperform the others if it had been used for calibration and evaluation (if it were available on the same periods), so I am not sure this point holds. It is true that consistency is important, but perhaps the gain would be much more if the resolution was also highly increased.
21. General comment: How are NOAA and ERA related? i.e. I imagine they must share a lot of the same historical data for the period prior to 1970-ish. It might be good to give more details on these in the data section.
22. In the Author contribution section, there is PB and OD, but I imagine OD = LO?
Overall a good work that could be much more impactful with a few adjustments, so I recommend minor revisions at this stage since I do not think it will require redoing simulations (although perhaps sampling high-quality datasets as subsets from the existing ones could be done with not too much work).
Citation: https://doi.org/10.5194/hess-2024-336-RC1 -
RC2: 'Comment on hess-2024-336', Anonymous Referee #2, 20 Jan 2025
The paper seeks to explore the applicability of two long term reanalysis datasets for reconstructing river flows (low, mean and high) across a large sample of European catchments. This is an important topic for understanding variability and change and contextualising emerging trends and will thus be of interest. I enjoyed reading the paper. While supportive of the paper and ultimately I recommend only minor corrections there are some adjustments to structure and a couple of points of clarity that in my mind would make the paper stronger.
- The title might be reframed to explicitly include the words ‘exploring’ or ‘evaluating’ the utility of these datasets across the flow regime. This is ultimately what the paper does. For a full reconstruction additional uncertainties including hydrological model would need to be included and many of the limitations noted in the discussion integrated into the analysis. However, if the aim is to evaluate the utility of these products then the current study design stands.
- The introduction and literature review provides a nice summary and collection of useful references.
- Rather than NOAA and ERA please use the full reanalysis product name throughout for clarity.
- Line 81 suggest evaluate rather than document
- In your aims on line 86, what does efficient mean, use of the word here is a little vague.
- Given the scale mismatches can you offer a sentence or two on why downscaling or a combination of downscaling and bias correction was not included?
- The section on the four criteria used for catchment selection (line 121) could be shortened with the actual criteria introduced as you list them. I found myself wondering what you mean by relatively long series, adequate area etc. Why the threshold of 100km?
- No need for bullets in differentiating catchment set.
- The model calibration process is generally well described, however it might be worth noting how parameter sets were identified – what search was used – the default in GR4J package or another approach.
- A single module structure is used across a very diverse catchment set. Some reflection on why and the strengths/weaknesses of this approach in the context of the aim of the paper would be useful in this section.
- Maybe introduce the Wilcoxon rank test in the methods and why it is used.
- Fig 7 and eslewhere – have you any suggestions as to why the reanalysis datasets diverge at particular points – eg. Western France prior to 1940 while they show comparable performance for more recent periods. Might there be differences in the sea level pressure data assimilated in each?
- In the discussion the limitation might be framed better in the context of the aims of the study, i.e. Full exploration of these aspects was not the purpose of the study but rather to evaluate the input datasets.
- Results are presented throughout the discussion section. It would be better for the reader and the clarity of the paper if these were in the results section.
- The conclusion is rather like a discussion to me. It would be better if the core research questions were discussed in the discussion section and then more concise conclusions drawn. This would help the sharpness and clarity of the paper.
Citation: https://doi.org/10.5194/hess-2024-336-RC2
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