the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Soil moisture droughts in Belgium during 2011–2020 were the worst in five decades
Abstract. In recent years, Belgium has experienced a sequence of intense droughts with wide-ranging impacts across multiple sectors. Determining whether these events are unprecedented or within natural variability requires indicators that properly diagnose drought. Root-zone soil moisture is a suitable indicator because it integrates meteorological forcings with land-surface processes. In Belgium, however, operational monitoring relies mainly on precipitation-based indices and lacks long-term in-situ soil-moisture observations, leaving uncertainty about whether these indices capture the persistence of root-zone drought. To address this gap, we reconstructed daily root-zone soil-moisture dynamics over Belgium for 1970–2020 using the mesoscale Hydrologic Model (mHM), placing recent droughts in historical context and evaluating the adequacy of precipitation-based indicators for representing drought conditions. Our analysis shows that droughts in 2011–2020 were unprecedented in both duration and severity over the past five decades. Between 2011 and 2020, the country experienced a cumulative three years of drought (non-consecutive), representing 30 % of the decade, more than double the cumulative duration in each decade from 1981–2010 and about 1.5 times that of 1971–1980. We further find that the Standardized Precipitation–Evapotranspiration Index (SPEI), currently used operationally as a proxy for agricultural droughts in Belgium, underestimates the persistence of root zone droughts because it does not explicitly account for land-surface memory. Thus, by including soil moisture monitoring in drought assessment, residual stresses on agriculture and subsurface water, which can persist long after meteorological conditions have normalized can still be detected. This gives decision-makers a more realistic understanding of droughts and how to respond proportionately.
Competing interests: At least one of the (co-)authors is a member of the editorial board of Hydrology and Earth System Sciences.
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
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Status: open (until 08 Nov 2025)
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CC1: 'Comment on egusphere-2025-4526', Heye Bogena, 26 Sep 2025
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AC1: 'Reply on CC1', Katoria Lesaalon Lekarkar, 06 Oct 2025
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Dear Heye,
We thank you for pointing out omission of the proper citation of the ISMN data. We have now updated our manuscript with the proper acknowledgements of the individual data providers according to the instructions in the README file which accompanies the data upon download. Since some providers (e.g., BFG_Nw and ORACLE) do not have a DOI which we can use to cite the data, we have acknowledged them in the Acknowledgements section of the manuscript using the details provided in the README file.
Below is an extract of our updated manuscript referencing the ISMN data, with the citations included.Without long-term in situ soil moisture within Belgium to validate the soil moisture output of mHM, we expanded the model domain to cover parts of France, Germany and The Netherlands where soil moisture observations are available from the International Soil Moisture Network (ISMN) (Dorigo et al., 2021). From the ISMN, we used data from the following networks: COSMOS (Zreda et al., 2008), GROW (Xaver et al., 2020), TERENO (Bogena et al., 2018), BFG_Nw and ORACLE, all shown in Figure 2.
...Acknowledgements
We acknowledge the work of Jens Wilhelmi (BFG_Nw network) for providing data in support of the International Soil Moisture Network. We also acknowledge the work of Arnaud Blanchouin and the ORACLE team of the Institut national de recherche en sciences et technologies pour l”environment et l”agriculture, France in support of the ISMN.
Citation: https://doi.org/10.5194/egusphere-2025-4526-AC1
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AC1: 'Reply on CC1', Katoria Lesaalon Lekarkar, 06 Oct 2025
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RC1: 'Comment on egusphere-2025-4526', Anonymous Referee #1, 30 Oct 2025
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The manuscript reconstructs multi-decadal root-zone soil moisture over Belgium with mHM and characterizes drought events using an SMI-based framework, comparing them with precipitation-based indicators (SPEI-1/3). The central finding—that 2011–2020 is the driest decade since at least 1971—is relevant for Belgian drought monitoring and well aligned with broader European trends.
However, the presentation is currently hard to follow due to (i) too many metrics without a clear hierarchy for ranking drought severity. (ii) Several methodological elements (MPR, KDE→SMI percentiles, Fisher-z, NSE definition, event splitting/merging rules) need one-line clarifications so readers can reproduce and interpret results.
1. The title can be read as if only 2011–2020 is analyzed, yet the study reconstructs 1970–2020 and concludes that 2011–2020 is the driest decade of the five. Please revise the title.
2. Provide a simple, explicit severity ranking protocol. At present the Results toggle between TDM, SMI≤τ area, exposure months, peak area, duration, SPEI-1/3, etc., without a decision rule. Readers cannot tell which event is “most severe.” Please state a clear hierarchy.
Add a Table listing the top events with: TDM, peak area (%), duration, exceptional-class exposure.
Annotate TDM values directly in Fig. 5 and state in the caption which tie-breaker decided final ranks when two events are similar.
3. Lines 363-365, is 2016–2017 or 1975–1977 drought bigger? And based on which indicators?
Lines 411-414, based on drought persistence, 2011-2020 is the biggest one.
4. Lines 365 and 367, when you talk about area percentage, provide the figure reference.
5. Lines 368–372 discuss 2022–2023, but your decadal analysis ends in 2020. Please remove or move to Discussion/SI with an explicit caveat.
Also line 341 says Fig. 5 covers 1970–2023, but the figure appears to show 1970–2020—please make the figure and caption consistent with the text.
6. Add a short description about each subsection at the start of Results. Two–three sentences will prevent readers from getting lost.
7. Lines 196-199, explain why resolutions differ.
8. Define NSE on first use (Results 3.1.2). Give the range and interpretation (≈1 perfect; ≈0 equals mean-flow benchmark; <0 worse than mean).
9. Lines 470-475, restate the minimum overlap area rule used to merge adjacent months into one multi-temporal event. Or how do you define duration. This clarifies whether a brief wet interlude (e.g., March–April 2017) splits or does not split an event.
10. MPR, what is the full name?
11. Terminology clarity. The manuscript uses three different concepts that contain the word “calibration”:
(i) a 5-year warm-up: is it 1965–1969, if yes, why exclude 1970 as a calibration year for drought analysis?
(ii) excluding 1970 as a calibration year for drought analysis when forming decades (hence using 1971–1980),
(iii) streamflow parameter calibration (2000–2023) vs validation (1970–1999).
Please clarify these three meanings to avoid confusion.
Citation: https://doi.org/10.5194/egusphere-2025-4526-RC1 -
AC2: 'Reply on RC1', Katoria Lesaalon Lekarkar, 30 Oct 2025
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Dear reviewer,
Thank you for your constructive feedback and suggestions on the manuscript.
We will start addressing them within the shortest time possible and share our responses to each of the queries raised.
With best wishes,
Katoria Lekarkar, on behalf of all authorsCitation: https://doi.org/10.5194/egusphere-2025-4526-AC2
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AC2: 'Reply on RC1', Katoria Lesaalon Lekarkar, 30 Oct 2025
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In this paper, data from the International Soil Moisture Network (ISMN) were used; however, the Terms and Conditions were not followed. Specifically, the rule on acknowledgement and citation was disregarded, which states:
"Whenever data distributed by the ISMN are used for publication, the data's origin (i.e., the original data provider and the ISMN) must be acknowledged and referenced. A reference to both the ISMN and all networks providing data for the study in question shall be given."