the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 22 May 2026
Hydrological spatial coupling within an abandoned Mediterranean terraced microcatchment
Abstract. Runoff (R) generation in Mediterranean headwater catchments is highly episodic and shaped by the interplay of precipitation (P), seasonal soil moisture (SM) dynamics, and terrain structure. In terraced landscapes, land abandonment has driven a forest transition that increases fuel loads and wildfire occurrence, while legacy features such as stone walls modify storage and flow pathways, affecting hydrological spatial coupling. Wildfires further reduce vegetation cover, induce soil water repellence, and lower infiltration capacity, enhancing R generation and reorganising connectivity during a post-fire window of disturbance, but their interaction with terrace structure at event scale is poorly understood. This study investigates how P, seasonal evolving SM, and terrain structure control R in a 4.7 ha terraced microcatchment in Mallorca, Spain, affected by a high-severity wildfire in 2013. Hydrological conditions were classified into four periods (wet, drying-down, dry, and wetting-up). P, SM, and discharge (Q) were continuously monitored over four years (2021–2024), with SM measured at representative hillslope and terrace locations. Of 186 P events analyzed, only 17% generated measurable outlet Q, with R highly concentrated in time: November 2021 alone accounted for 73% of total R volume. Maximum SM consistently emerged as the strongest indicator of R occurrence across seasons, while event-scale changes in SM (ΔSM) were particularly informative during transitional periods; antecedent SM showed limited predictive power, especially under partially coupled conditions. Hillslopes responded rapidly to P but with weak coupling between local SM and outlet Q, whereas farm terraces exhibited storage-controlled behaviour in well-connected positions and delayed or suppressed responses in disconnected mid-terrace areas. Overall, R emerges from the interaction between P forcing, dynamically evolving SM, and spatially variable structural connectivity, rather than from static thresholds, highlighting the need for connectivity-aware, event-scale approaches to inform land management in Mediterranean landscapes under global change.
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 29 Aug 2026)
- RC1: 'Comment on egusphere-2026-2711', Anonymous Referee #1, 30 Jul 2026 reply
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RC2: 'Comment on egusphere-2026-2711', Federico Gómez-Delgado, 08 Aug 2026
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Please find my full referee comment in the attached pdf supplement.
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Summary
This manuscript reports on four years (2021–2024) of continuous data collection on precipitation, soil moisture, and outlet discharge from a 4.7-hectare burned terraced microcatchment in Mallorca. The authors examine 186 rainfall events, including both runoff-producing and non-runoff events, to explore how rainfall characteristics and antecedent soil moisture affect runoff generation and how landscape position shapes the relationship between local soil moisture and catchment discharge.
Overall, I found this to be an interesting and worthwhile contribution. The dataset itself is especially valuable. Multi-year, event-based monitoring in abandoned Mediterranean terraced catchments is uncommon, particularly in systems displaying extremely low runoff coefficients and little or no baseflow. Equally important is the deliberate inclusion of non-flow events, which are often excluded from similar studies despite providing essential information on threshold behaviour and catchment response. This is, in my opinion, one of the strongest aspects of the study.
The manuscript fits well within the current connectivity literature, and the Introduction provides a useful overview of key concepts and previous research. Overall, the analyses are clearly presented and the figures are informative.
However, several of the principal conclusions appear to extend beyond what the current analyses can robustly support. Many results rely on descriptive comparisons between event groups, whereas the manuscript often adopts predictive or mechanistic language. There is considerable potential to strengthen the paper through additional analysis and a more cautious interpretation of the findings. The issues outlined below are all addressable, and resolving them would substantially improve the manuscript.
General comments 1. Interpretation of soil moisture metrics
One aspect that deserves further consideration is the interpretation of maximum soil moisture and ΔSM as indicators of runoff occurrence.
In the manuscript (see Abstract, Sections 3.2 and 4.1.2), maximum soil moisture is presented as the strongest indicator of runoff, whereas antecedent soil moisture appears less important. However, both maximum SM and ΔSM are measured during the rainfall event and therefore evolve concurrently with runoff. They are thus not independent predictors, but responses to the same rainfall forcing that produces runoff.
Could the authors discuss this distinction more explicitly? In particular, to what extent do maximum SM and ΔSM provide information beyond rainfall magnitude itself?
Interestingly, one of the most informative findings may instead be that antecedent soil moisture—the only true pre-event state variable—shows relatively weak predictive capability in this catchment. This differs from several earlier studies (e.g., Penna et al., 2011; Llorens et al., 2018) and may deserve greater emphasis.
To better support the conclusions, I encourage the authors to examine whether soil moisture metrics retain explanatory value once rainfall characteristics are considered. For example:
The Introduction refers to developing a “probabilistic understanding” of runoff occurrence, yet the manuscript does not currently include an event-probability model. Such an analysis could provide a much stronger quantitative basis for the conclusions.
2. Event independence and temporal clustering
The dataset covers four years, but most runoff-producing events occurred within a relatively short period, particularly during autumn and winter 2021. November 2021 alone contributed a large proportion of the total runoff.
This raises an important question concerning statistical independence. To what extent do the reported differences represent general catchment behaviour rather than the unusual hydrological conditions associated with this period?
It would therefore be helpful if the authors could:
Such a sensitivity analysis would strengthen confidence that the reported relationships reflect general catchment behaviour rather than one exceptional hydrological period.
In addition, some seasonal groups contain very few runoff events. Although the statistical tests may be suitable in principle, the limitations associated with small sample sizes should be discussed and seasonal significance interpreted cautiously.
3. Comparison of absolute soil moisture thresholds
I also encourage the authors to reconsider the interpretation of absolute soil moisture thresholds across different monitoring locations.
The manuscript states that factory calibration is suitable for identifying thresholds across sites. Using identical sensors certainly facilitates temporal comparisons at an individual location; however, direct comparison of absolute volumetric water content among sites with contrasting stone content, carbonate content, and fine-earth fractions is more challenging.
Could the authors clarify why they consider absolute values directly comparable under these conditions?
An alternative would be to express thresholds in normalized terms, for example using site-specific percentiles or scaling relative to each sensor’s observed range. This would retain the spatial interpretation while reducing uncertainty associated with absolute calibration. If site-specific calibrations are available, including them would considerably strengthen these comparisons.
4. Assessment of hydrological coupling
I encourage the authors to reconsider how hydrological coupling is evaluated in Section 3.3.2.
The current analysis focuses on periods when outlet discharge is already occurring (Q > 0) and examines the associated range of local soil moisture conditions. While this provides useful information about the conditions under which runoff was observed, it is less clear whether it fully characterizes hydrological coupling itself.
Could the authors discuss how often similar soil moisture states occurred without measurable outlet flow? Including this complementary perspective would help distinguish whether the observed variability reflects differences in coupling strength or simply the temporal evolution of soil moisture during runoff events.
Would it also be possible to complement the current analysis with event-scale lag analysis, cross-correlation, or soil moisture–discharge hysteresis analysis (e.g., following Zuecco et al., 2016)? Such analyses would provide a more direct assessment of the timing and strength of hydrological coupling and would considerably strengthen this section.
5. Role of wildfire in the study
The wildfire provides important context for the study site, but its role within the analyses appears more limited than suggested by the Abstract and Introduction.
The manuscript discusses post-fire hydrological processes, including soil water repellency, infiltration changes, and the post-fire disturbance window. However, monitoring began approximately eight years after the 2013 wildfire, and the analyses do not explicitly include burn severity, recovery status, or comparisons with unburned conditions.
Could the authors clarify the intended role of wildfire within the manuscript? If wildfire is primarily included as background context, I suggest moderating the framing in the Abstract and Introduction so that it more closely reflects the analyses that were performed. Alternatively, if information on burn severity or recovery patterns is available, incorporating it into the analyses could further strengthen the manuscript.
6. Interpretation of runoff generation mechanisms
The Discussion presents several plausible explanations for the observed behaviour, including subsurface lateral flow, fill-and-spill processes, terrace storage, and activation of slower subsurface pathways.
These interpretations are certainly consistent with the observations, but the available measurements consist primarily of soil moisture at two depths and outlet discharge. Without complementary observations such as piezometers, tracer experiments, runoff pathway measurements, or direct observations of overland flow, it may be difficult to distinguish among the different runoff-generation mechanisms.
I therefore encourage the authors to present these mechanisms more explicitly as hypotheses supported by the observations rather than definitive interpretations.
In addition, the two high-intensity dry-season runoff events appear particularly interesting. Could these events represent a different runoff-generation mechanism, perhaps involving infiltration-excess runoff, compared with the wetter-season events? Discussing this possibility may strengthen the paper by highlighting the state-dependent nature of runoff generation within the catchment.
7. Discharge measurements and event classification
Given the very small annual runoff volumes reported for this catchment, it would be helpful to provide additional information regarding discharge detectability and the consistency of the discharge measurements throughout the monitoring period.
The manuscript notes that the stage sensor was replaced in January 2023, but it is not entirely clear whether the two sensors were cross-calibrated or whether the minimum detectable discharge remained unchanged. Because the classification of events into runoff and non-runoff depends directly on detecting measurable discharge, additional clarification would strengthen confidence in the event catalogue.
Specifically, it would be useful to:
Similarly, the 27 August 2023 event appears to be one of the few runoff-producing storms during the dry season. Although discharge could not be quantified, acknowledging more explicitly how its exclusion may influence the seasonal analyses would improve transparency.
8. Sensitivity of the event catalogue
The conclusions of the study depend on several methodological choices used to define individual rainfall events, including the minimum rainfall threshold, the event separation criterion, and the time window used to associate rainfall with runoff.
These choices are reasonable, but it would be valuable to know how sensitive the principal findings are to alternative definitions.
Would it be possible to perform a brief sensitivity analysis using, for example, different minimum rainfall thresholds (1, 2, or 5 mm)? Demonstrating that the principal conclusions remain similar under alternative event definitions would increase confidence in the robustness of the results.
9. Structural versus hydrological connectivity
The manuscript classifies monitoring locations using the Index of Connectivity, which is based primarily on surface topography and sediment transport pathways.
The Discussion, however, largely interprets the observed behaviour in terms of subsurface storage and lateral flow processes. Because these processes are not necessarily represented by a topography-based connectivity index, it would be helpful to discuss this distinction more explicitly.
Could the authors elaborate on why the Index of Connectivity is considered an appropriate proxy for structural hydrological connectivity in this terraced environment? Alternatively, framing these classes primarily as topographic positions rather than hydrological connectivity classes may avoid potential ambiguity.
10. Consistency of terminology
The manuscript discusses several closely related concepts, including hydrological spatial coupling, hydrological coupling, functional connectivity, and hydrological connectivity.
Although these terms are introduced in the Introduction, they appear to be used somewhat interchangeably throughout the manuscript. Establishing a consistent terminology and applying it throughout would improve clarity and help readers distinguish among the concepts being discussed.
Similarly, the manuscript appropriately highlights the value of including non-runoff events. However, since studies such as Saffarpour et al. (2016) and Kaffas et al. (2025) have also incorporated non-runoff events, it may be more accurate to describe this as an area that remains relatively underexplored rather than presenting it as a completely novel aspect of the study.
Specific comments
Concluding remarks
Overall, I believe this manuscript has the potential to make a valuable contribution. Its principal strength is the unique multi-year, event-resolved dataset, particularly the inclusion of non-runoff events that are rarely retained in comparable studies.
At present, however, the manuscript uses causal and probabilistic language that the analysis does not yet fully support. The revision path is relatively clear: (1) fit an event-occurrence model and test whether soil moisture metrics add information beyond rainfall forcing; (2) directly address the dependence on the November 2021 event cluster; (3) use normalized or calibrated soil moisture thresholds across sites; (4) add lag or hysteresis analysis to substantiate the coupling claims; and (5) adjust the wildfire framing to match the analyses performed.
Most of the revisions suggested above are analytical rather than editorial, but they build directly on an already valuable dataset and should substantially strengthen the manuscript. With these changes, the paper could make a strong contribution to the connectivity literature and provide a useful benchmark dataset for connectivity-aware modelling. I would be pleased to review a revised version.