| 10 Nov 2025
Drought dynamics across the hydrological cycle – an extensive validation of the National Hydrological Model of Denmark
Abstract. Droughts are gaining attention in temperate regions, as underscored by the severe European droughts of 2018 and 2022. In Denmark, these events caused widespread agricultural losses, degradation of surface waters and ecosystems, and infrastructure damage from soil subsidence. Although historical drought trends in northern Europe are uncertain, climate projections indicate more frequent and intense droughts. Hydrological drought propagation from precipitation deficit to soil moisture, streamflow and groundwater is shaped by topography, soil, vegetation, hydrogeology, and human activity. While streamflow and soil moisture droughts have been widely studied, groundwater droughts remain underexplored despite their importance for baseflow and water supply. In Denmark, where groundwater and surface water are closely linked, and groundwater resources are heavily relied upon, an integrated approach to drought assessment is essential. In this study, we compile a high-quality observational dataset, including soil moisture, streamflow, and groundwater levels, to systematically evaluate model-simulated drought and its propagation throughout all hydrological compartments by the National Hydrological Model of Denmark (DK-model), an integrated, distributed hydrological model. The DK-model’s nationwide coverage, combined with Denmark’s dense hydrological monitoring network, enables a detailed assessment of the model’s ability to simulate drought events. This includes model skill in reproducing observed anomalies, drought response times, and propagation dynamics. The DK-model was found to reproduce drought indices very well for groundwater levels and streamflow compared to respective observational time series. For soil moisture, model performance was lower. Drought propagation, evaluated by accumulation periods for precipitation with optimal correlation to hydrological drought, is likewise reproduced well for streamflow and groundwater. In contrast, the model struggles with the soil moisture signal. By evaluating the DK-model’s performance in simulating drought propagation, this study contributes to improving large-scale hydrological drought modelling and enhances the understanding of the strengths and weaknesses of this approach, while increasing its potential for drought analysis, monitoring, and forecasting. The findings provide critical insights into drought dynamics in temperate regions and support sustainable water resource management in a changing climate.
Manuscript: egusphere-2025-5373
Journal: Hydrology and Earth System Sciences (HESS)
Title: Drought dynamics across the hydrological cycle – an extensive validation of the National Hydrological Model of Denmark
Authors: Raphael Schneider, Simon Stisen, Mark F. T. Hansen, Mie Andreasen, Bertel Nilsson, Klaus Hinsby, Hans Jørgen Henriksen, and Ida Karlsson Seidenfaden
Summary:
This manuscript presents a comprehensive and innovative evaluation of the DK-model for drought monitoring across multiple hydrological compartments. The authors compile an extensive observational dataset and analyse drought propagation from meteorological to soil moisture, streamflow, and groundwater droughts. This represents a substantial effort and addresses a highly relevant topic for hydrological drought research. The manuscript fits well within the scope of _Hydrology and Earth System Sciences_ and will be of interest to a broad readership.
The paper tackles an important problem and is based on a unique national-scale modelling and observational dataset. The main strengths are the comprehensive evaluation across hydrological compartments and the explicit focus on drought propagation. The main weaknesses concern (i) manuscript structure, (ii) conceptual clarity regarding drought definitions and thresholds, and (iii) limited quantitative discussion of model limitations and comparison to existing studies.
The study is generally well presented, with clear figures and a comprehensive modelling framework. However, the manuscript is currently quite lengthy and would benefit from a clearer separation of results and discussion, as well as a more in-depth discussion of the findings in comparison to other hydrological modelling systems used for drought assessment. After addressing the comments below, the manuscript would be suitable for publication.
Major Comments:
1 Manuscript structure and focus on drought evaluation
The manuscript would benefit from a clearer structure and stronger focus on the core drought-evaluation results. In particular:
- The selection and quality assurance of observational data should be moved fully into the _Methods_ section as data preprocessing.
- Detailed descriptions of observational datasets and preliminary performance results should be moved to the Appendix.
- This restructuring would shorten the manuscript and sharpen the focus on drought-related findings.
- Model performance results (e.g. Figure 1) are shown for all available stations, whereas drought evaluation is conducted only for a selected subset. For consistency and relevance: Performance results should be shown only for the stations used in the drought analysis. Results for all stations can be provided in the Appendix.
3. Definition of drought and drought thresholds
Drought is repeatedly defined as index values below 0, which corresponds to “dry anomalies” rather than drought. Drought classes are introduced in the Introduction, but only values <0 are analysed later.
- Please clarify the conceptual definition of drought used in the study.
- Why are thresholds for moderate or severe drought (e.g. SPI < −1) not analysed?
- Please ensure consistency between definitions, analysis, and interpretation.
4. Separation of results and discussion
Results are repeatedly introduced and interpreted in the Discussion section.
- All new results should be presented in the Results section.
- The Discussion should focus on interpretation, comparison with previous studies, and implications.
- Several subsections currently labelled as Discussion (e.g. Sections 4.2 and parts of 4.3) read as Results.
5. Discussion depth and comparison to other models
The discussion is relatively short compared to the breadth of the analysis.
- Please extend the discussion by comparing the DK-model performance to other hydrological models used for drought assessment (e.g. national-scale or continental-scale models).
- Strengths and limitations of the DK-model relative to these systems should be discussed more explicitly.
Specific Comments:
- “Climate projections indicate more frequent and intense droughts” (p.1, LL10):
For Northern Europe, projected drought changes are mixed in the literature. Please nuance this statement (e.g. more summer droughts, fewer winter droughts).
- Abstract (LL21–24):
Statements on model performance are very general. Please include quantitative results.
- p.3, LL71–74:
You state that fewer studies address groundwater and the entire hydrological cycle, yet cite more studies than for other compartments. Please clarify.
- p.4, LL100:
“Weichsel and Saale” – please clarify that these refer to glaciations.
- p.5, LL145:
Is there a more recent reference describing developments over the last three decades?
- p.5, LL154–155:
How thick is the unsaturated/root zone in the model? This is essential for interpreting soil moisture results.
- p.6, LL189–190:
Please quantify the impact of constant abstraction rates and provide supporting material (Appendix). A map showing trends in water consumption (Appendix) would help identify regions where this assumption is most critical.
- p.7, LL215:
Which lag times were tested?
- p.7, LL219–220:
Please clarify the criteria used for expert judgement in data evaluation.
- p.9, LL256ff:
Only introduce indices actually used in the study and explain why they were chosen over alternatives.
- p.9, LL275:
SPI values between 0 and −1 are not drought. Please correct and add references for drought class definitions.
- p.10, LL285:
Why are SMDI and SDI resampled from weekly to monthly?
- p.10, LL289–290:
Are results of the normality test shown?
- p.11, LL305:
Please specify the length of soil moisture time series.
- p.12, LL342:
Interpretation (“little bias”) should be moved to the Discussion and compared with literature.
- p.12, LL344–345:
A mean absolute error of 0.65 m relative to an average amplitude of 1.06 m appears large. Please discuss.
- Figure 1 (p.13):
Show performance only for stations used in drought analysis.
- p.13, LL356:
Consider renaming to “Quality-assured observational dataset for drought evaluation”.
- p.13, LL358:
Figure numbering and narrative would be clearer if the study area and data were introduced before calibration results.
- p.17, LL400–401:
Statements regarding reduced correlation during drought periods should be quantitatively tested and better explained.
- p.17, LL406:
Drought index <0 does not equal drought.
- p.19, LL435:
The colour coding of wells is already explained in the text; repetition is unnecessary.
- p.20, LL440:
Testing accumulation periods up to 60 months for soil moisture with only ~10-year records is not meaningful. Consider limiting this to ~36 months.
- p.25, LL507:
Why was May 2020 chosen? Please provide context.
- p.26, LL518–520:
The discussion starts very generally; consider linking more directly to your results.
- p.26, LL523:
The key research question should already be clearly stated in the Introduction.
- p.26, LL530:
Statements about future soil moisture observations are vague—please provide references or concrete examples.
- p.29, LL611–612:
Please specify the thickness of the root zone. Given that the modelled soil moisture represents the entire unsaturated zone (i.e. a larger volume than observations), one might expect the opposite behaviour.
- Please explain this discrepancy more clearly.
- p.31, LL656–658:
The model does not appear to capture soil moisture lag times well. Please adjust this statement accordingly.