Detecting the resilience of soil moisture dynamics to drought periods as function of soil type and climatic region

Aqel, Nedal; Groh, Jannis; Weihermüller, Lutz; Gründling, Ralf; Carminati, Andrea; Lehmann, Peter

doi:10.5194/egusphere-2025-5141

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https://doi.org/10.5194/egusphere-2025-5141

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24 Oct 2025

| 24 Oct 2025

Status: this preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).

Detecting the resilience of soil moisture dynamics to drought periods as function of soil type and climatic region

Nedal Aqel, Jannis Groh, Lutz Weihermüller, Ralf Gründling, Andrea Carminati, and Peter Lehmann

Abstract. Abrupt changes in climatic conditions and land management can cause permanent shifts in soil hydraulic response to climatic inputs, impacting soil functions and established soil–climate interactions. To quantify the resilience of soil water content dynamics after abrupt changes in environmental conditions, we present a model framework combining a neural network with seasonal trend analysis (STL). Using data from a series of lysimeters from the TERrestrial ENvironmental Observatories (TERENO) – SOILCan lysimeter network, we identified changes in soil water content responses after an extremely hot and dry summer in Germany in 2018. The model incorporates meteorological variables decomposed into seasonal and long-term components along with a categorical indicator of current moisture conditions. It is trained on data from a reference site with stable soil water content response and applied to lysimeters from multiple origins exposed to contrasting climates. By analysing annual residual patterns—particularly mean bias over time—soil water content state dynamics is classified as ‘stable’, ‘resilient’, or ‘changed’, reflecting whether the system maintains, recovers, or diverges from its original state. We found that soils preserve the response function to environmental forcing under typical conditions but exhibit structural change when relocated to new environments, even when soil texture remains constant. The proposed method offers a scalable and non-invasive tool for tracking changes in the response of soil water content to climatic change and provides early indicators of changes in essential soil functions and soil health status.

Received: 16 Oct 2025 – Discussion started: 24 Oct 2025

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Nedal Aqel, Jannis Groh, Lutz Weihermüller, Ralf Gründling, Andrea Carminati, and Peter Lehmann

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RC1:
'Comment on egusphere-2025-5141', Anonymous Referee #1, 19 Nov 2025 reply
This paper applies statistical modelling techniques (combining a neural network model with seasonal trend analysis) to a comprehensive dataset of soil water contents and pressure potentials measured at 10 cm depth in lysimeters moved to two different locations, in order to identify shifts in hydrological responses to climate forcing.
The shifts in these “in situ” water retention curves (WRC) are intriguing and really quite dramatic (e.g. figures 4, 7 and 8). But I do wonder about the mechanisms and underlying processes. The authors are rather vague about the causes, suggesting that they are due to changes in soil structure tiggered by climate (lines 674-676). I’m not fully convinced about this interpretation, not least because the largest changes seem to occur in the very dry range of the WRC where structure should not play such a large role.
(in this respect, I think the WRC curves should be plotted with matric potential on a log-axis for improved readability. On a linear scale, we can’t really see what is happening close to saturation, which is where most of the structural changes would be expected).
There may be alternative explanations for the observations, including (slowly reversible) swell-shrink behaviour and preferential (non-equilibrium) flow. I would encourage the authors to try to strengthen the discussion and interpretation of the data with respect to the underlying mechanisms, including the above-mentioned processes. Nevertheless, although the responses to climate of apparent WRC observed by the authors “in situ” seem stronger than I would expect (especially in the dry range), I am aware of two previous large-scale (regional-continental) statistical analyses of water retention curves measured in the laboratory that have shown significant impacts of climatic factors on the structural pore space (Hirmas, D. et al. 2018, Nature 561, 100-103; Klöffel, T., et al., 2024. Geoderma, 442, 116772). These studies could be mentioned as they would give support to the authors’ inferences and interpretations.
Specific comments
Line 40: “indicator” rather than “factor”?

Lines 40-41: “Dominant”? This seems a bit far-fetched. I don’t think soil water content at 10 cm depth is the best hydrological indicator of soil health. It could certainly indirectly reflect risks of surface runoff, but then surely surface runoff itself would be a much better indicator of soil health? Contrary to claims made in the paper, I don’t think water content so close to the soil surface says so much about the supply of water to plants (rooting depth and water availability in deeper soil layers will be far more important). I think the authors should tone down the emphasis in the introduction of the relevance of this kind of study to soil health.

Lines 42-43: these three papers are not cited in the reference list

Line 50: Or (2020) is not in the reference list

Line 51: I don’t understand how a modelling approach can be destructive? This should be clarified.

Line 77: I think you could also cite Robinson et al. (2019) here (Global Change Biology, 25, 1895-1904).

Lines 79-81: It may not be related to only soil structure. What about wettability (hydrophobicity)? Could that also play a role at these time scales? Perennial vegetation can also adapt to climate change. One example comes from an earlier modelling study based on the TERENO SoilCan data (see Jarvis et al. 2022. Hydrology and Earth System Sciences, 26, 2277-2299).

Lines 92-93: this statement is disproved by the following sentence (and also by the author’s work). I think this sentence should be deleted (nothing important is lost).

Line 93: The authors of this paper are incorrectly specified in the reference list.

Line 113: No need to start a new paragraph here.

Lines 250-252: this seems very subjective. Why choose these percentiles and these scores? How were they chosen, presumably by trial and error?

Line 371: write “water contents” rather than “values” (if I understood correctly)

Line 425: “differently” not “different”

Line 426: this seems too speculative. You don’t know that it is related to structure. Maybe you could write “….which may indicate”

Line 444: “that” not “who”

Lines 582-586: This is interesting, but the authors neglect the fact that WRC’s measured in the laboratory do show strong correlations with texture across large regions showing strong climate contrasts. This empirical support for texture-based estimates of the WRC is really very strong, especially in the dry region of the WRC. How can you reconcile your results with this past experience and knowledge?

Line 600: this is much too speculative. You need to write this more carefully (“may have”). There are other more plausible interpretations. It could simply be that hydraulic conductivity at and close to saturation has increased. Near-surface water contents during rainfall events of any given intensity would then be smaller. It could also be a consequence of “by-pass” water flow in shrinkage cracks.

Line 636: what is meant by “functional integrity”?

Lines 643-645: yes, especially if they are statistical models. Isn’t it reasonable to expect that physics-based models might perform better outside the training data?

Lines 650: The extent to which the subsoil is exploited by roots should be much more important for plant water supply than the surface 10 cm.

Minus signs (for matric potential) are missing on all the WRC plots

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Citation: https://doi.org/10.5194/egusphere-2025-5141-RC1
EC1: 'Handling editor comment on egusphere-2025-5141', Nunzio Romano, 12 Jan 2026 reply

Dear Authors,
As the handling editor, I would like to offer a few comments that should be discussed, especially for the benefit of readers, potential discussants, and assigned reviewers.
First, let's consider the term "resilience" employed in the current submission. This concept is used in a variety of ways in different contexts. Here, the authors classify soil-water content dynamics as “stable”, “resilient”, and “changed’, depending on changes to the soil-water content profile from its original state (Lines 21-24). I suggest framing this classification more consistently with existing literature, because using the term “resilient” alongside “stable” and “changed” could be misleading. In the hydrological and environmental sciences, resilience is generally accepted as the ability of a system (a lysimeter in this paper) to withstand disturbance, to maintain its functions, whether potential or actual, (which a bit reflects the concepts of resistance or vulnerability), and the system’s recovery rate following disturbance (e.g., Lal, 1997; Pimm, 1984; Gunderson and Holling, 2002). Using the available data in the present submission, it would be interesting to quantify the rate of recovery. Overall, the concepts of resistance, recovery time, and recovery rate should be addressed, I guess.
Anyhow, at line 342, the authors correctly argue that "... it is still possible that the response function may recover in the future ...". However, this important statement is then lost as the text progresses, whereas it should be reiterated at least in the conclusions.
The other comment refers to the authors’ statement on Line 653, I quote: “… This response depends on soil hydraulic properties …”. Of course, the impact that different local climatic conditions, soil being equal, exerts on the dynamics of soil-water content in the lysimeter also depends on changes in soil organic carbon and microbial activity. These latter two aspects seem to be overlooked in this submission. Since the authors claimed to have measured both soil-water content and matric potential, it would be interesting to examine how soil-water retention and hydraulic conductivity functions changed over the investigated period. It is plausible that any changes are mainly attributable to changes in soil organic matter. Another related issue is demonstrating that changes in soil particle arrangement did not occur due to transportation from one site to another.

References cited
Gunderson, L.H., C.S. Holling (eds.), 2002. Panarchy. Washington (DC), 507 pp., Island Press.
Lal, R. 1997. Phil. Trans. R. Soc. Lond. B 352, 997-1010.
Pimm, S.L. 1984. Nature 307, 321-326.

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Citation: https://doi.org/10.5194/egusphere-2025-5141-EC1

Nedal Aqel, Jannis Groh, Lutz Weihermüller, Ralf Gründling, Andrea Carminati, and Peter Lehmann

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Nedal Aqel, Jannis Groh, Lutz Weihermüller, Ralf Gründling, Andrea Carminati, and Peter Lehmann

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Short summary

This study investigates how soils respond to major climatic disturbances, such as the extreme drought in Germany in 2018. Using long-term lysimeter observations and an artificial intelligence model, we show that persistent shifts in soil water dynamics indicate changes in hydraulic properties that may affect soil health, emphasizing the need for continuous monitoring under a changing climate.


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