the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 05 May 2025
Hysteresis between groundwater and surface water levels indicates the states of hydrological turnover affecting solute transport and redox processes
Abstract. Small streams are highly sensitive to variations in discharge, a sensitivity predicted to increase in future climate scenarios, impacting ecological health of streams and water management practices. Prolonged low-flow conditions alter groundwater-surface water (GW-SW) exchange patterns, leading to extended losing phases and a reduced duration of gaining periods. This study examines the relationship between hydrological turnover (HT) and hysteresis patterns under various system states in a third-order tributary of the River Mosel in Trier, Germany, using high-resolution hydrological and chemical data collected over two years.
Our results reveal distinct seasonal dynamics in GW-SW exchange. Counterclockwise hysteresis, prevalent during summer and drought conditions, was linked to the expansion of the hyporheic zone and bank storage, which reorganizes flow paths and influences redox dynamics. We established a strong correlation between HT and hysteresis characteristics, identifying the h-index as a valuable diagnostic tool for tracking seasonal changes in GW-SW connectivity, storage and hyporheic zone behavior based on hydraulic preconditions.
As climate change intensifies drought conditions, the hyporheic zone will play a vital role in solute cycling and GW-SW connectivity. The h-index, combined with chemical and hydrological monitoring, provides a robust framework for understanding and predicting these dynamics in small stream ecosystems.
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CC1: 'Comment on egusphere-2025-1674', Nima Zafarmomen, 08 May 2025
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The manuscript presents a valuable, two-year data set that links hysteresis behaviour (h-index) to hydrological turnover (HT) and redox-sensitive chemistry in a third-order stream. The topic is timely, and the field evidence is strong. With clearer framing, tighter statistics and leaner figures, the study could make a solid contribution to hydrology and eco-hydrology journals.
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Explicit objectives.
The Introduction motivates the study but never states concrete research questions or hypotheses. Add a short paragraph (or numbered list) at the end of the Introduction that spells out exactly what you test or demonstrate. -
Causality vs correlation.
Several conclusions—such as counter-clockwise hysteresis proving hyporheic expansion—are inferred from correlations. Either soften the causal language or supply additional evidence (e.g., time-lag analysis, hydraulic modelling) that directly links loop direction to flow-path reversal or bank-storage volume. -
Drought sample size and treatment.
Only nine drought events are analysed, yet they underpin strong statements. Provide confidence intervals (bootstrapping would suffice) or, alternatively, fold drought events into a broader “low-flow” class and discuss the limitation. -
Statistics and multiple testing.
Pearson, Spearman, and Wilcoxon tests are referenced, but p-values and effect sizes are scattered, and no correction for multiple comparisons is mentioned. Consolidate the statistical results in one concise section, report effect sizes, and apply a correction such as Holm–Bonferroni where you test several correlations simultaneously. -
Figure overload and clarity.
Figures 2, 4, 6, and 7 pack in many axes, symbols and colours. Some panels duplicate information already shown elsewhere. Split oversized figures, move supporting plots to the Supplement, use a single colour palette across all figures (e.g., winter = blue, summer = orange, drought = red) and increase font sizes. -
Chemical interpretation depth.
The simultaneous presence of nitrate, manganese and iron is intriguing but only briefly noted. Expand the Discussion to explore residence times, lateral mixing, and implications for nitrate removal or metal mobilisation under overlapping redox zones. -
Consistency in terminology and units.
The manuscript alternates between “hydrological turnover,” “turnover” and “HT [% m⁻¹].” Likewise, hysteresis direction is described as clockwise/anticlockwise in some places and positive/negative h in others. Define the terms once, specify units clearly, and stick to a single vocabulary throughout.
Please also consider citing “Assimilation of Sentinel-based Leaf Area Index for Modeling Surface-Groundwater Interactions in Irrigation Districts”. That study demonstrates how remotely sensed vegetation parameters—specifically Sentinel-derived LAI—can be assimilated into coupled surface–groundwater models to improve estimates of evapotranspiration and return flows in irrigated landscapes. Referencing it would (i) situate your h-index/HT framework within the broader move toward multi-sensor data integration and (ii) underscore the relevance of vegetation dynamics when interpreting seasonal GW–SW connectivity, especially under drought or low-flow conditions
Citation: https://doi.org/10.5194/egusphere-2025-1674-CC1 -
AC1: 'Reply on CC1', Lars Bäthke, 14 May 2025
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We thank the commenter Nima Zafarmomen for the detailed and constructive feedback. Below we respond to the points raised:
- Objectives and hypotheses
The Introduction motivates the study but never states concrete research questions or hypotheses. Add a short paragraph (or numbered list) at the end of the Introduction that spells out exactly what you test or demonstrate.
We agree that explicit objectives improve clarity. We will add a paragraph at the end of the Introduction section stating our specific hypotheses regarding hysteresis direction and hydrological turnover.
“The objective of this study is to explore how seasonal changes in hydraulic conditions influence groundwater–surface water interactions in a headwater stream. We hypothesise that (1) the direction and magnitude of hysteresis between groundwater and stream water levels are indicative of seasonal hydrological states, and (2) the hysteresis index is related to hydrological turnover and reflects the degree of hyporheic exchange, consequently affecting water chemistry.”
- Causality vs. correlation
Several conclusions—such as counter-clockwise hysteresis proving hyporheic expansion—are inferred from correlations. Either soften the causal language or supply additional evidence (e.g., time-lag analysis, hydraulic modelling) that directly links loop direction to flow-path reversal or bank-storage volume.
We acknowledge the reviewer’s concern and have revised the manuscript to avoid overstating causality where only correlative evidence is available. We replaced causal terms such as “proves” or “demonstrates” with “suggests,” “indicates,” or “is associated with” where appropriate. These changes were made in the Abstract (lines 12–13),
“Counterclockwise hysteresis, prevalent during summer and drought conditions, coincides with conditions indicative of hyporheic zone expansion and bank storage, potentially affecting flow paths and redox dynamics.”
Discussion (lines 316–317, 327),
“This may be indicative of a hyporheic response occurring during early infiltration phases.”
“Counterclockwise hysteresis and high hydrological turnover are associated with enhanced riparian bank storage.”
and Conclusion (line 370),
“Our findings suggest that hysteresis behavior can serve as an indicator of changes in hyporheic zone dynamics associated with hydrological turnover, particularly during summer droughts.”
where the connection between hysteresis direction and hyporheic expansion was previously framed in causal terms.
- Drought sample size
Only nine drought events are analysed, yet they underpin strong statements. Provide confidence intervals (bootstrapping would suffice) or, alternatively, fold drought events into a broader “low-flow” class and discuss the limitation.
Within our sampling campaign, nine events were conducted under exceptionally low-flow conditions. We classified these as “drought” events, as discharge fell below the 5th percentile of the five-year streamflow record at our observation site. This threshold-based classification aligns with standard hydrological drought definitions and was supported by concurrent low-flow observations at the downstream catchment gauging station (>10 a). To investigate differences in system behavior across hydrological states, we grouped events into winter, summer, and drought categories and tested for statistical significance using non-parametric methods. We applied a 95 % confidence level and will clarify this in the Methods section. Figure 5 will be updated to reflect these confidence intervals.
- Statistics
Pearson, Spearman, and Wilcoxon tests are referenced, but p-values and effect sizes are scattered, and no correction for multiple comparisons is mentioned. Consolidate the statistical results in one concise section, report effect sizes, and apply a correction such as Holm–Bonferroni where you test several correlations simultaneously.
We applied a Holm–Bonferroni correction where multiple comparisons were made. We will refer to the correction method in the manuscript accordingly.
- Figures
Figures 2, 4, 6, and 7 pack in many axes, symbols and colours. Some panels duplicate information already shown elsewhere. Split oversized figures, move supporting plots to the Supplement, use a single colour palette across all figures (e.g., winter = blue, summer = orange, drought = red) and increase font sizes.
We appreciate the feedback regarding figure complexity. While we aim to retain the current number of figures to preserve coherence in the main text, we will revise Figures 2, 4, 6, and 7 to improve readability. This includes increasing font sizes, unifying the color palette, and removing redundant visual elements where possible. We believe these adjustments will improve clarity without compromising the completeness of the data presentation.
- Chemical Interpretation Depth
The simultaneous presence of nitrate, manganese and iron is intriguing but only briefly noted. Expand the Discussion to explore residence times, lateral mixing, and implications for nitrate removal or metal mobilisation under overlapping redox zones.
Thank you for highlighting this. We will expand the discussion section to better interpret the simultaneous presence of nitrate, manganese, and iron. We will explore how overlapping redox zones may arise from lateral mixing and variable residence times and discuss the implications for nitrate removal and metal mobilization. We will refere in the manuscript to additional studies, such as Kaufman, M. H., M. B. Cardenas, J. Buttles, A. J. Kessler, and P. L. M. Cook (2017), Hyporheic hot moments: Dissolved oxygen dynamics in the hyporheic zone in response to surface flow perturbations, Water Resour. Res., 53, 6642–6662, doi:10.1002/2016WR020296 and Briggs, M. A., F. D. Day-Lewis, J. P. Zarnetske, and J. W. Harvey (2015), A physical explanation for the development of redox microzones in hyporheic flow, Geophys. Res. Lett., 42, 4402–4410, doi:10.1002/2015GL064200, discussing the dynamic nature of typical streams and rivers driving equally dynamic redox conditions in the hyporheic zone.
These additions help clarify the biogeochemical significance of the observed solute patterns under different hydrological conditions.
- Consistency in terminology and units
The manuscript alternates between “hydrological turnover,” “turnover” and “HT [% m⁻¹].” Likewise, hysteresis direction is described as clockwise/anticlockwise in some places and positive/negative h in others. Define the terms once, specify units clearly, and stick to a single vocabulary throughout.
We agree that consistent terminology improves readability. Throughout the manuscript, we will consistently refer to “hydrological turnover (HT)” and specify it with the unit [% m⁻¹] upon first mention. For hysteresis, we will define the relationship to positive/negative h-index values early in the Methods section.
- Suggested citation of Sentinel-based study by Nima Zafarmomen
Please also consider citing “Assimilation of Sentinel-based Leaf Area Index for Modeling Surface-Groundwater Interactions in Irrigation Districts”. That study demonstrates how remotely sensed vegetation parameters—specifically Sentinel-derived LAI—can be assimilated into coupled surface–groundwater models to improve estimates of evapotranspiration and return flows in irrigated landscapes. Referencing it would (i) situate your h-index/HT framework within the broader move toward multi-sensor data integration and (ii) underscore the relevance of vegetation dynamics when interpreting seasonal GW–SW connectivity, especially under drought or low-flow conditions.
While we appreciate the suggestion and recognize the relevance of remote sensing for hydrological studies, the focus of Zafarmomen et al. (2024) on model-data assimilation in irrigated systems differs substantially from our process-based approach in a non-irrigated headwater stream. As such, we chose not to include this reference to maintain focus on directly related work.
Thank you again for the helpful suggestions, which significantly improved the clarity and robustness of our manuscript.
Citation: https://doi.org/10.5194/egusphere-2025-1674-AC1
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