the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 04 Dec 2025
Large impact of extreme precipitation on projected blue-green water shares
Abstract. Precipitation partitioning into blue and green water resources is a fundamental hydroecological process shaping freshwater availability. This partitioning is determined by interactions among climatic conditions, land surface characteristics, and vegetation dynamics, which change with rising temperatures and CO2 concentrations. Yet, global shifts in blue and green water shares and their management implications remain uncertain. We address this knowledge gap using climate simulations to quantify the relative partitioning of precipitation into green and blue water flows and its controlling factors. Here, we show that extreme five-day precipitation primarily drives partitioning shifts, favouring larger blue water shares. This effect is independent of baseline precipitation increases and generates larger blue water shares under both drying and wetting conditions. Additionally, interactions between leaf area index and plant water-use efficiency strongly impact regional partitioning trends. Our results translate shifts in blue-green water partitioning into an impact-relevant perspective, providing actionable context for water and land management.
Competing interests: Some authors are members of the editorial board of journal ESD.
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.- Preprint
(3311 KB) - Metadata XML
-
Supplement
(17469 KB) - BibTeX
- EndNote
Status: open (extended)
- RC1: 'Comment on egusphere-2025-5896', Josephin Kroll & Rene Orth (co-review team), 31 Jan 2026 reply
Viewed
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 213 | 93 | 21 | 327 | 48 | 23 | 18 |
- HTML: 213
- PDF: 93
- XML: 21
- Total: 327
- Supplement: 48
- BibTeX: 23
- EndNote: 18
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
Review of Heselschwerdt et al., egusphere-2025-5896
“Large impact of extreme precipitation on projected blue-green water shares“
This study investigates the partitioning of precipitation into runoff and transpiration, and its changes through this century. The authors introduce a new metric to describe this partitioning and use output of Earth system model simulations to determine the partitioning and its changes until the end of the century throughout the globe. They identify hot spot regions where precipitation is mainly partitioned into runoff or transpiration, respectively, and regions with strongest projected changes in the partitioning. Finally, they attribute the partitioning changes mainly to changes in extreme precipitation and vegetation and derive management implications.
-------------------
Recommendation:
We think the paper requires major revisions.
The topic of this study is interesting and timely. Ongoing global change affects climate and vegetation in various ways, and their complex interplay modulates the water cycle. This way, major water fluxes such as runoff and transpiration may change differently, and for partly different reasons. The precipitation partitioning metric introduced by the authors in this paper summarizes relevant water cycle changes beyond individual variables, including an attribution of the resulting spatial patterns of change. This analysis presents a relevant contribution because it helps to identify regions with relevant water cycle changes, and proposes related mechanisms that require additional attention in further research.
However, before the paper can be published we would ask the authors to consider the concerns described below:
--------------------
General comments:
Related to this, lines 34-61 provide interesting mechanistic background on precipitation partitioning, which, however, is not connected to the rest of the introduction. So we suggest either to shift this to the discussion section, or connect it more to the introduction to motivate the relevance and knowledge gap in the topic.
Furthermore, while extreme precipitation is identified as a main control of trends in blue-green water shares, this may not be well represented by Earth system models. For example, a recent study found that the current rather coarse resolution of data from climate and earth system models, as also used in this study, underestimates the impact of such extremes (Brunner et al. 2025).
Related to this, we appreciate the indication of model uncertainty in Figures 2-4. However, this is not really visible in the maps in Figures 2b-d and 4, and missing in Figure 1. Maybe consider to make this more prominent – or even to introduce a masking to avoid showing results in regions where (i) models disagree or (ii) models disagree with reference products in Figure S1, in order to avoid interpreting results in regions where uncertainties actually largely prevent this. This could also enhance the accuracy of the attribution analysis in Figure 3.
We do not wish to remain anonymous - joint review by Rene Orth and Josephin Kroll.
We have notified the editor of our collaborations with Peter Greve and Lan Wang-Erlandsson.
------------------
Specific comments:
Line 4: given that this is the abstract, maybe replace blue/green water shares with a more generally understood terminology
Line 4: Climate simulations → Earth system model simulations (this also applies to other mentions of climate simulations throughout the manuscript)
Line 8: according to the results in Figure 3 it is leaf area index and water use efficiency individually rather than their interaction that influences the partitioning
Line 12-16: this motivation of the relevance of precipitation partitioning is very brief, would expand this
Line 21: “stabilises Earth system” is unclear
Line 23: “climate regulation” is unclear
Line 27: "critical water functions” is unclear
Line 54: "vegetation activity” is unclear
Line 57: "runoff-consuming sinks” is unclear
Line 80: required variables are unclear at this point
Line 114: Good point about the non-closure of the water balance. See our recent paper Huang et al. for this. (sorry for the self-promotion)
Line 120: The term ‘climate indices’ does not fit the chosen variables/indices. For example, (i) RX5day is not calculated over a period that would refer to climate (~30 years), (ii) VPD is not an index, and also not referred to over a period considered as climate, (iii) WUE is not representing climate, but rather vegetation characteristics. An alternative could be ‘hydroecological variables’ as used in the manuscript before
Line 163: Explain more clearly in this section that this attribution analysis is done for the spatial patterns rather than for the temporal changes in each grid cell or region. Also emphasize this in the discussion of Figure 3 that you are not directly attributing the temporal changes of the partitioning shown in Figure 2 but merely the spatial patterns therein, where determined drivers are not necessarily the same for both.
Line 170: Would start this section with this paragraph.
Line 192: “destroyed” → ”removed”
Line 192/193: not sure we get the point here
Line 195: Can you comment on the consideration of lateral flow in the models, and its potential role for the partitioning?
Line 199-201 & 326 & elsewhere: The results section incorporates interpretation/discussion already such that it would be more clear to adapt the title to ‘Results and Discussion’ and remove ‘Discussion and’ from the title of section 4.
Line 202: unclear what’s meant with absolute BGWS values and whether it is referring to model-mean data or observation-based results
Line 207: why interpret regions with large baseline biases at all?
Line 209: Would start the section with this paragraph.
Line 215: Unclear to which average ‘below-average’ is referring - global?
Lines 231/232: There are no visible patterns in the Sahara.
Line 233: unclear what’s the difference between saturation excess vs. infiltration excess
Line 244: Can/Should you assume broadly similar soil properties across rainforests?
Line 257: section 3.2 seems a bit convoluted and was harder to follow: suggestion to rather summarize the main possible mechanisms and then mention example regions instead of selecting regions and describing those
Line 265: Fig. 2: place legend in panel a on top or below as for the other figures; brings space for spatial average subpanel
Line 268: ‘strongly linked’ suggests causality, which cannot be derived from covariance across space
Line 342: increases instead of ‘is increasing’
Line 351: blue-to-green shift is of similar magnitude, why is this not covered in the text?
Line 352: Actually this section is about implications rather than management. There is little discussion about land or water management measures and strategies. Either revise this section, or drop the management from the title here, and also adapt the wording in the abstract in line 9 (“impact-relevant”, “actionable”).
Line 355: One could ask why it matters where the next rain drop goes in the presence of little to no rain in some regions
Line 368: insert Δ before changes as done in the lines below
Line 385: I wonder about the causal direction here: are transpiration increases supporting vegetation productivity or does increased vegetation productivity induce/come with increased transpiration?
Line 387: Figure 5: this is rather a table than it is a figure. For a figure, I would suggest to make two x-y graphics, having dR or dT on the y-axis and dBGWS on the x-axis. Insert text in the respective 4 panels of the graph
Line 392: ‘sizeable areas’ is unclear
Line 398: ‘environmental flows’ is unclear
– Figure 1: The content of section 3.1 mainly describes and discusses results in the light of the i) water-energy-limitation framework as well as ii) the role of extreme precipitation. Hence, Figure 1 should include maps illustrating the three BGWS features - energy-limited partitioning, water-limited partitioning, precipitation-intensity related partitioning - and the ratio of RX5day/mean precipitation (so fig. S5a). This would make the figure more in line with the title of the manuscript, which emphasizes the role of extreme precipitation and follows the explanation used in the text. Finally, it would be good to cite some more related literature such as Seneviratne et al., 2010 and Denissen et al. 2022.
– Figures 1 and 2: Adjust color bar range across panels b–d in both figures.
– Figure 3: Do the boxes in panels a and b show the spread of the attribution results for the individual Earth system models? Also, panels c and d are not described and discussed in the text. For example, (i) y-axis unclear, response to what?, and (ii) what is the meaning of the lines connecting ‘end-of-century response’ across predictors, especially as the y-axis scale changes. Instead, you could use boxplots and depict individual models by differently colored dots or differently shaped points; +/- dBGWS could be indicated by outline of each dot/symbol or by making two boxplots per predictor.
– Figure S1: Labelling of panels in the caption is not in line with the figure.
– You could consider adding summary statistics to the maps in the figures as also stated in the text.
References:
Orth, R. and G. Destouni 2018: Drought reduces blue-water fluxes more strongly than green-water fluxes in Europe. https://doi.org/10.1038/s41467-018-06013-7
Huang, H. et al. State-of-the-art hydrological datasets exhibit low water balance consistency globally, doi: 10.5194/essd-2025-376
Séférian et al. 2019: Evaluation of CNRM Earth System Model, CNRM-ESM2-1: Role of Earth System Processes in Present-Day and Future Climate. https://doi.org/10.1029/2019MS001791
Seneviratne et al. 2010: Investigating soil moisture–climate interactions in a changing climate: A review. https://doi.org/10.1016/j.earscirev.2010.02.004
Denissen et al. 2022: Widespread shift from ecosystem energy to water limitation with climate change. https://www.nature.com/articles/s41558-022-01403-8
Brunner et al. 2025: A global perspective on the spatial representation of climate extremes from km-scale models. https://doi.org/10.1088/1748-9326/ade1ef