Articles | Volume 25, issue 8
https://doi.org/10.5194/nhess-25-2783-2025
© Author(s) 2025. This work is distributed under the Creative Commons Attribution 4.0 License.
Groundwater recharge in Brandenburg is declining – but why?
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- Final revised paper (published on 19 Aug 2025)
- Preprint (discussion started on 03 Feb 2025)
Interactive discussion
Status: closed
Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor
| : Report abuse
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RC1: 'Comment on egusphere-2025-222', Anonymous Referee #1, 06 Mar 2025
- AC1: 'Reply on RC1', Maik Heistermann, 12 May 2025
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RC2: 'Comment on egusphere-2025-222', Anonymous Referee #2, 28 Apr 2025
- AC2: 'Reply on RC2', Maik Heistermann, 12 May 2025
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) (13 May 2025) by Katrin Nissen
AR by Maik Heistermann on behalf of the Authors (15 May 2025)
Author's response
Author's tracked changes
Manuscript
ED: Referee Nomination & Report Request started (16 May 2025) by Katrin Nissen
RR by Anonymous Referee #1 (27 May 2025)
ED: Publish as is (28 May 2025) by Katrin Nissen
ED: Publish as is (01 Jun 2025) by Maria-Carmen Llasat (Executive editor)
AR by Maik Heistermann on behalf of the Authors (02 Jun 2025)
This is a very interesting paper that analyses the groundwater recharge behavior in 5 catchments in Brandenburg. The paper fits very well within the scope of the special issue.
I think the paper has great potential, but it is somewhat hindered by missing information and lacking methodology descriptions. This makes the paper somewhat difficult to follow, I often had to backtrack quite a lot in the text to see if I missed some detail or information. Therefore I am sending below my recommendations to improve the manuscript.
My main question is about the model setup. Are the models set up on a per catchment basis, or over a grid or other spatial sub-units? This was very confusing to me – sometimes I was sure everything is aggregated over catchments, but in some parts further inhomogeneities were resolved. It would be important to include more details about this in the text. Please find my specific comments below.
Specific comments:
L33: These few paragraphs could use some references to support the text.
L36: groundwater
L42: Does the term “combination” here means a gauging station after multiple rivers join together?
L50: can you provide a reference?
L52: what about cross-flow with lower aquifer layers? The recent study of Tsypin et al., 2024 showed that deeper layers interact with the uppermost at certain geological settings, mainly where the Rupelian clay layer is eroded. These flows could act as a water source or sink as they flow upwards or downwards at different locations.
Tsypin, Mikhail, et al. "Modeling the influence of climate on groundwater flow and heat regime in Brandenburg (Germany)." Frontiers in Water 6 (2024): 1353394.
Fig.1: Which wells were used to create this map? Is the data coverage homogeneous, or are there any areas with fewer information?
This figure would be a better place to show the used gauge locations than fig. 5.
L67: “any long term trend in discharge can thus be interpreted as a long term trend in GWR.”
Can you elaborate on this a bit further: what is the long-term criteria, why short term changes cannot be used in such way? Is there a model that can show this behavior/or a past study where this was investigated?
L108: reference to the dataset
L125: reference needed
L129: Can you support this statement with a reference, or by referring back to the introduction
L136: What does partly mean here?
L143: I am just curious here: what about not interpolated, but dynamically downscaled datasets, such as CERv2 (https://www.tu.berlin/klima/forschung/regionalklimatologie/mitteleuropa/cer) . Would they not be a better choice for gridded data?
L161: parenthesis missing
Were there any weighting used when multiple gauges were included? I think using a buffer area as a criteria here could easily introduce further uncertainties to the data (as precipitation in Brandenburg could be very heterogeneous, especially during extreme rainfall events) – does including them make a big difference? (does it worth it to use them instead of just the climate station)
L196: The used dataset is a categorized dataset for groundwater distance. Does its non-continuous nature create any issues for your analysis?
General question for methods: Was the analysis done over a grid, over catchment or any other spatial unit? It is not clear for me from the text
Also, for a better comprehensibility, this section could really use a flowchart on how the different parameters interact, or even a conceptual figure on how the modeling concept looks like.
L214: I really like this concept for filling in missing data.
Can you give more details on how this package was used (as it is a specific module for photovoltaic modelling, it is not straightforward how to use it in this setting). Which function was used for modelling with what parameters?
L228: same question: what random forest model was used and how?
L266: How did you check that this spin up period was enough for the model?
L270: was the modelling run on a grid? – I am really confused about this at this point
L282: why was this setup needed?
Table3: this table is a bit complicated and difficult to understand. Please consider revising it.
L320: maybe: “(small triangles)”
Figure 4: can you add a legend instead of explaining everything in the captions?
L318: are the blue/red lines are simply drawn by connecting the points of the corresponding LAI setup?
L327: This could also be referred to as a linear relation between precipitation and GWR
L338: Can you explain further how the significance was calculated?
Figure 5: This figure is very complex, but I think the chosen visualizations are really the best way to show the findings. You could make the figure a bit less busy by removing the gauge locations from the map. Also positioning the legend next to the map is not ideal.
Could you consider adding another figure where (some of – maybe just the main configuration) the modelled GWR timeseries are shown against the discharge timeseries for the catchments? It would help the text in my opinion…
L351: rephrase “While this is plausible…”
L361: what are the blue and red lines, are they trendlines or just connectors between the points?
L365: which offset? Could you be more exact?
Can one state here that there is an unknown water loss from the system as the discharge trend is steeper?
L370: Does it mean more humid conditions or a faster change towards humid conditions?
L373: point out whiskers on the legend
L380: where was this pointed out?
How could the model have GWR estimations for different depths – was it over a grid?
5 limitation and uncertainties: I really like this section, but it could have a more exact title like “Explaining the gap between trends”
L437: a similar behavior was pointed out locally by Somogyvari et al., 2024 for a lake system in the region.
Somogyvári, Márk, et al. "A hybrid data-driven approach to analyze the drivers of lake level dynamics." Hydrology and Earth System Sciences 28.18 (2024): 4331-4348.
They also used a combination of different factors as an explanation for system water loss, together with an environmental tipping point. Did you consider such explanations?
L511: Could you rank the different explanations based on plausibility?