the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Quantifying the response of water and carbon balances to land cover and climate extremes across Germany
Abstract. Land cover and extreme weather events are closely connected to water yield and carbon sequestration. Understanding the tradeoffs between carbon and water and how they respond to human disturbances is critical for quantifying ecosystem services. The monthly scale ecosystem model, WaSSI, was tested and applied across Germany for mapping carbon and water balances from 2001–2019. We estimated that Germany generates 84.86 billion m3 of discharge and sequesters 106.03 Tg of carbon annually. The eastern states were comparatively drier than the rest of the country, as most of their precipitation was lost as evapotranspiration. Croplands, urban areas and Evergreen Needle Forests (ENF) provide 82.5 % of the water yield, while the forests sequester the major share of carbon (56.3 %) altogether. The results highlight the importance of sparse land covers (e.g. wetlands) in carbon sequestration. Findings also suggest that national water yield and carbon balances are sensitive to extreme events. In 2002 and 2013, due to high precipitation, the stocks of key ecosystem services were notably higher. Similarly, during the drought years of 2003 and 2018, the services were reduced drastically, but we found that buffers from the previous year played an important role in mitigating negative impacts. This study highlights that, when integrated with local data, a relatively simple modelling approach is adequate to answer questions of coupled water and carbon responses to climatic variability at a large scale. We conclude that land management of both forests and croplands are vital to sustain ecosystem services under a changing climate.
- Preprint
(3634 KB) - Metadata XML
-
Supplement
(686 KB) - BibTeX
- EndNote
Status: open (until 08 Oct 2025)
- RC1: 'Comment on egusphere-2025-1629', Anonymous Referee #1, 29 Sep 2025 reply
-
RC2: 'Comment on egusphere-2025-1629', Anonymous Referee #2, 01 Oct 2025
reply
In this manuscript, the authors validate the WaSSI (Water Supply Stress Index) model for the case of Germany. Since this model has typically been applied to other study areas (i.e., the conterminous United States, Mexico, Rwanda, and Burundi), this application represents an innovative contribution. The study is also valuable in clarifying some of the dynamics behind the spatial and temporal variations of the ecosystem services considered in the study area. Nevertheless, a number of gaps are present, and taken together, they make it difficult to fully understand the methodologies and the results described in this work. In particular, some points and logical steps would benefit from a more detailed explanation in order to strengthen the overall clarity and robustness of the study. My review mainly focuses on these aspects.
In conclusion, I consider the manuscript suitable for publication, provided that the general revision suggested are carefully addressed.
General comments
- While reading the manuscript, I had the impression that the term “flood” is sometimes used to refer to a “high precipitation event” (e.g., line 372) or an “extremely wet year” (e.g., line 297). However, the term “flood” typically refers to the inundation resulting from an excess of water that causes normally dry areas to be submerged. It does not simply indicate heavy rainfall events or periods of above-average precipitation. I would therefore suggest reviewing the manuscript to ensure that the term “flood” is used correctly and, where necessary, replacing it with more precise terms or expressions.
- I think it would be important to consistently include references to the datasets used in the text. I would therefore suggest checking this aspect throughout the manuscript—for example, at line 164 (FLUXNET2015) and line 177 (MOD17A2HGF).
- Referring to Figure 4c, I found it a bit difficult to understand how, in some areas, actual evapotranspiration could exceed potential evapotranspiration. For readers who are not experts on the topic, the intuitive expectation would be that actual evapotranspiration is less than or equal to potential evapotranspiration. It might be worthwhile to explain and comment on this difference between the two variables, as this could help readers better follow the results.
- I believe that certain essential details are missing in the description of the procedures, particularly in some steps that are crucial for understanding the methodology. Specifically, the following aspects would benefit from further elaboration:
- Lines 145-146: a more detailed explanation of what the quality checks consisted of could improve the clarity of both the procedure and the results.
- Lines 158-160: for transparency and clarity, it could be helpful to provide further details about why those specific stations were selected, why not more were included, and how the choice of different stations might affect the results.
- Lines 164-165: a short explanation of how corrections and gap filling were carried out could be useful.
- Results and Discussion Section lack some important steps and information. These missing elements are essential to fully grasp the reasoning that supports the results and to properly assess their applicability in different contexts:
- In the Discussion section, I did not find any direct reference to Figure 6. It might be useful to elaborate on and comment on this figure, since it is the only one showing the temporal evolution of the variables considered.
- I think that from the presentation of the results, it is not clear how “buffers developed from the previous year can play a significant role in mitigating this effect”, particularly when discussing the sensitivity of ecosystem services to extreme events (lines 318–319). I believe it would be important to elaborate on this point in the Results section and, if possible, refer to the corresponding figures in the Discussion chapter.
- Line 320: it may be useful to further clarify why the model can be applied to the whole Central Europe. As it is currently written, it is not entirely clear how the procedures and conclusions could also be applied to areas beyond the specific study region (i.e., Germany).
Specific comments
- I am not very familiar with the WaSSI model, and I found it challenging to fully understand what it is and how it works. While some information is provided, it appears scattered across different parts of the manuscript. I think that an initial, more comprehensive presentation of the model—beyond what is already included—would be very helpful to better frame the analyses and to facilitate the interpretation of the results. This could include its main aim, the study areas considered, the way it operates, and other relevant details.
- In the abstract, a lot of results are described and explained. I think it might be helpful to more clearly highlight the main novelties and contributions introduced by this work.
- Please consider adding a section describing the study area (climate, land use, etc.)
- Line 15: you may consider briefly clarifying what is meant by “ecosystem services” for readers less familiar with the concept.
- It would improve readability if acronyms were defined when they first appear in the text. For example, “MODIS” and “CGLS” (lines 125 and 127) are introduced without prior definition.
- Line 141: providing a short explanation of why exactly 10 classes were chosen, and whether you considered different numbers, might help clarify the procedure.
- Line 145: including the number of removed pixels could be an informative detail.
- Lines 165-169: this section might be difficult to follow for readers less familiar with the topic. Expanding the explanation with more details could make it clearer.
- In Section 3.1, I think it would be very helpful to include a comparison between the performance metrics obtained for the different variables (discharge, ET, GPP) in this study and those reported in the literature from other studies applying the same or similar models (if available). Providing this context could help to better clarify the results and support the applicability of the WaSSI model to new study areas.
- Figure 2: adding a legend to indicate the meaning of the two colours could improve the clarity of the plots.
- Figure 4: you may consider including in the figure the names of the regions mentioned in the text, or finding a way to highlight them. This would make the reading and the analysis of the figure much easier.
- Lines 316-319: referring explicitly to the relevant tables/figures in the text could make the discussion clearer.
- Lines 324-327 and 333-336: a more detailed explanation of the influence of the different factors could add clarity.
- Line 339: explaining why results are weaker for the Lackenberg Forest station, or what the reasons can be, could improve transparency.
- Line 340 and 341: the meaning of the terms “complex” and “complicated” in this context is not entirely clear; considering alternative synonyms or more specific wording may help.
Technical comments
- I warmly suggest to check that the figures are accessible also for readers with colour-vision deficiencies. Alternative colour scales might improve clarity.
- Figure S1: you might consider modifying the colour scale (as noted above) and/or using different marker shapes for each category to increase readability.
- Please double-check punctuation when separating sentences across the manuscript. In some cases, a full stop is missing (e.g., line 36, between “interconnected reasons” and “two of them”), while in others a full stop is used where a comma or similar punctuation might be more appropriate (e.g., line 53, before the sentence starting with “Which negatively affects”). In my opinion, this would strongly improve the readability of the manuscript.
Citation: https://doi.org/10.5194/egusphere-2025-1629-RC2
Viewed
HTML | XML | Total | Supplement | BibTeX | EndNote | |
---|---|---|---|---|---|---|
1,207 | 33 | 17 | 1,257 | 25 | 28 | 28 |
- HTML: 1,207
- PDF: 33
- XML: 17
- Total: 1,257
- Supplement: 25
- BibTeX: 28
- EndNote: 28
Viewed (geographical distribution)
Country | # | Views | % |
---|
Total: | 0 |
HTML: | 0 |
PDF: | 0 |
XML: | 0 |
- 1
Pyarali et al. simulate how different land cover types and climate variability – wet and dry years – modulate multiple ecosystem processes and services using the Water Supply Stress Index (WaSSI) model in Germany. The study contributes to understanding the spatio-temporal variability of the provision of key ecosystem services such as water yield and carbon sequestration, as well as their anomalies during extreme wet and dry years, at a national scale, using an ecosystem model that simulates the coupling between water and carbon cycles. Additionally, the manuscript can provide new insights into the potential loss of ecosystem services provision under future climate projections in Germany.
While the manuscript is well written and organized, I see some issues that, in my view, need to be addressed before it can be considered for publication in HESS. Specifically: (i) I found it difficult to follow the description of the model evaluation given the limited level of detail provided on validation; (ii) the manuscript would be strengthened by a more explicit discussion of how the areal extent of each land cover type influences the provision of ecosystem services; (iii) the characterization of extreme wet and dry years is based only on precipitation anomalies, which I find too narrow.
Major comments:
Minor comments:
Technical corrections: