the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 02 Sep 2024
Delayed Stormflow Generation in a Semi-humid Forested Watershed Controlled by Soil Water Storage and Groundwater
Abstract. An analysis by Cui et al. (2024) of stormflow responses to rainfall in a mountainous forested watershed in the semi-humid regions of North China identified a distinct threshold for bimodal rainfall-runoff events, where delayed stormflow appeared to be influenced by shallow groundwater. This study further investigates the processes driving these bimodal events, focusing on the dynamics of soil water content (SWC) and groundwater level (GWL) during storm events. The results show that delayed stormflow is governed by the interplay between SWC and GWL. Delayed stormflow is initiated when SWC exceeds the soil’s water storage capacity, while its timing and volume are determined by GWL fluctuations. During rainfall, SWC increases rapidly; if it does not reach the soil's water-holding capacity, it stabilizes after the rainfall ends. Conversely, if SWC surpasses the soil's storage capacity, it decreases rapidly post-rainfall, with the excess rainwater infiltrating deeper to recharge groundwater, leading to a gradual rise in GWL. As GWL rises, increased hydraulic conductivity facilitates the movement of shallow groundwater into the stream channel, resulting in delayed stormflow. Simultaneously, the effective connection area between the stream channel and adjacent hillslopes expands vertically. At specific high GWL thresholds, GWL responses across the watershed converge, significantly increasing groundwater discharge and reducing lag times, often causing the delayed stormflow peak to merge with the direct stormflow peak. These findings enhance our understanding of delayed stormflow generation in similar regions and contribute to refining runoff generation theories.
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Status: final response (author comments only)
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RC1: 'Comment on egusphere-2024-2177', Anonymous Referee #1, 08 Nov 2024
This is a timely manuscript on the bimodal response of semi-arid catchments. This work is novel in that there is very limited work looking into the bimodal response in catchments and the threshold behaviours of these responses. While the authors provide a great deal of information on the processes and do a good job, there a few areas that need some work. Once done, it should be an excellent contribution to the field. My comments are attached in a separate file. My recommendation is major revisions.
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AC1: 'Reply on RC1', Zhen Cui, 29 Nov 2024
Specific comments
Comment 1:
Introduction: I would suggest that the authors include information on where the source of bimodal response come from based on the literature. It is not clear in the introduction if this is from groundwater, deep soil layers or if it a delayed response from the headwater component of the watershed.
Response 1:
Thank you for your insightful comment. We agree that it is important to clarify the sources of bimodal responses. This topic has been thoroughly reviewed and analyzed in our previous study (Cui et al., 2024), where we discussed the important contributions of old water (shallow groundwater) to bimodal response. To address your comment, we will provide a brief summary of its key findings to better contextualize the current research and added a reference to this study in the introduction.
Comment 2:
L70-71: This is a good point; however, you will need to explain why. Is it that most catchments only show a unimodal response or is it that when catchments show bimodal responses authors do not go into depth on these responses?
Response 2:
Thank you for your constructive comment. We appreciate the suggestion to further elaborate on why many studies fail to distinguish between unimodal and bimodal streamflow responses. To address this, we will revise the manuscript to include additional explanations supported by relevant literature. Specifically, we identified the following reasons:
The second peak in a bimodal response often occurs some time after rainfall has ended, whereas many studies focus only on streamflow changes during the rainfall event itself.
The occurrence of bimodal responses is closely related to the topographic and geological conditions of the catchment, and not all catchments exhibit this phenomenon.
The research focus varies, and most studies prioritize other hydrological processes over the classification of response types.
All these points will be added to the introduction to provide a clearer context for our argument. We believe this addition strengthens the rationale for our study and its contribution to understanding bimodal responses. Thank you again for your helpful suggestion.
Comment 3:
L78: Please include the full name of these acronyms (SWC, GWL) as it is the first time used in the main text.
Response 3:
Thank you for pointing this out. We will revise the manuscript to include the full names of the acronyms SWC (Soil water content) and GWL (Groundwater level) when they are first introduced in the main text. This change ensures clarity for readers.
Comment 4:
L116: Please expand on this. What are the specific depths that soil moisture is being measured.
Response 4:
Thank you for your insightful comment. We agree that providing more detail about the soil moisture measurement depths will improve the clarity and completeness of the manuscript. In response, we will revise the text to include the following details:
"On Hillslope 1, soil water content (SWC) was monitored at five locations along the slope, and three additional locations were monitored near WS900. At each site, SWC sensors were installed at 10 cm intervals, from the surface down to a depth of 80 cm. Measurements were recorded every 10 minutes."
Comment 5:
L158: Can you indicate why these three events were selected.
Response 5:
Thank you for your valuable comment. We appreciate your suggestion to elaborate on why these three events were selected. To address this, we will revise the manuscript to include the following explanation:
"Among the 95 rainfall-runoff events analyzed, these three events were chosen because they represent the three distinct patterns of soil water content (SWC) and groundwater level (GWL) variability identified in our study. These events effectively illustrate the dynamic interactions between SWC and GWL, making them highly representative. Moreover, all three events occurred within the same year, minimizing the potential influence of inter-annual variability on SWC and GWL responses."
Comment 6:
L162: Refer to Figure 3.
Response 6:
Thank you for your helpful suggestion. We agree that referencing Figure 3 at this point in the text will enhance clarity and provide direct visual support for the described phenomenon. We will revise the sentence as follows:
"During the early stages of these events, rainfall prompted a rapid rise in SWC, while GWL remained relatively stable (Figure 3)."
Comment 7:
L168-170: Indicate the amount of rainfall in both the text and the figure.
Response 7:
Thank you for your constructive suggestions. We will added the rainfall amounts for each event in the text and included these values in Figure 3.
Comment 8:
L172: Recommend putting arrows on these figures to show the evolution of the events. Also, please indicate what the red circles indicate.
Response 8:
Thank you for your constructive suggestions. We agree that adding arrows to indicate event evolution and clarifying the meaning of red circles will improve the clarity and informativeness of both the text and the figure. We will make the following revisions:
Arrows in Figure 3: We will add arrows to Figures 3a, 3b, and 3c to indicate the temporal evolution of the events, providing a clearer visualization of SWC and GWL changes during each event.
Explanation of red circles: We will clarify in the figure caption that red circles indicate periods of rainfall, while black circles denote post-rainfall periods.
Comment 9:
L173-174: Please indicate the depth of rainfall for these events.
Response 9:
Thank you for your comment. We agree that including the depth of rainfall for these events will enhance the clarity of the description. To address this, we will revise the text as follows:
"Figures 3b (57.2 mm rainfall) and 3c (95.2 mm rainfall) depict the dynamics of SWC and GWL during storm events, where a pronounced counterclockwise hysteretic relationship was observed."
Comment 10:
Figure 7: Please indicate the rainfall depths for these events.
Response 10:
Thank you for your thoughtful comment. We agree that rainfall depth is a critical factor influencing groundwater level (GWL) responses. However, we would like to clarify that Figure 7 is a schematic diagram designed to conceptually illustrate the two distinct types of GWL responses—quick and slow—during storm events, rather than representing specific rainfall-runoff events.
To address this potential confusion, we will add a statement in main text acknowledging that rainfall amount can significantly influence GWL dynamics and suggesting future studies to explicitly model this relationship.
Thank you for highlighting this aspect, which has helped us refine the manuscript.
Comment 11:
General analyses: In general, the analyses are quite good and I think good interpretations of the data have been presented. My one major concern which was not clear in the paper is if the analyses were based on the entire bimodal hydrograph or the second peak of the hydrograph. This needs to be made very clear in the manuscript. Additionally, it would be interesting to look at the threshold for the first peak and then compare it to the second peak. Furthermore, with the groundwater, and rainfall, it will be good to combine these with the soil moisture to provide a better estimation and explanation of the threshold e.g. Detty and McGuire 2010, Farrick and Branfireun 2014, Penna et al 2011.
Response 11:
Thank you for your thoughtful comment and for recognizing the quality of our analyses. We agree that it is essential to clarify whether our analyses focus on the entire bimodal hydrograph or specifically on the second peak. In response, we will revise the manuscript to clearly state that our study primarily focuses on the second peak of the hydrograph. While the first peak is a direct response to rainfall and occurs without fail, the second peak is influenced by factors such as rainfall amount and antecedent soil moisture conditions. These factors determine the threshold for the second peak's occurrence, which is the main subject of our investigation.
Furthermore, we acknowledge your suggestion to incorporate soil moisture, groundwater, and rainfall data for a more comprehensive estimation of the threshold. We will discusse how the combination of these variables effectively indicates the occurrence of the second peak, consistent with previous studies (e.g., Detty and McGuire 2010, Farrick and Branfireun 2014, Penna et al 2011). This relationship was preliminarily explored in our earlier work (Cui et al., 2024), whereas the current study delves deeper into the mechanisms underlying this threshold phenomenon.
These revisions will be included in the revised manuscript, and we appreciate your suggestion for improving the clarity and depth of our manuscript.
Citation: https://doi.org/10.5194/egusphere-2024-2177-AC1
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AC1: 'Reply on RC1', Zhen Cui, 29 Nov 2024
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RC2: 'Comment on egusphere-2024-2177', Anonymous Referee #2, 14 Nov 2024
This manuscript examines the runoff generation processes leading to delayed peaks and proposes a conceptual model for the Xitaizi Experimental Watershed (XEW), North China. Overall, this paper could have the potential to contribute to the literature, but I think improvements in the way of presenting the research questions, the results and discussion would help to highlight the unique aspects of this work.
In my opinion, the manuscript is strongly linked to Cui et al (2024), which has recently been published in HESS and addresses the “characteristics and occurrence” of bi-modal events in the same catchment (https://doi.org/10.5194/hess-28-3613-2024). This is a personal opinion, but I do not understand the strategy of publishing two independent papers instead of summarising key results in one. I understand the same dataset has been used in both and methods descriptions are very similar (or the same). The authors mention that the data will be made available in Zenodo at the time of publication. Does this mean that the data is different than https://zenodo.org/records/12581739? If yes, it would have been nice to make the data available.
I think the introduction could present better the significant amount of literature where the role of soil water content and groundwater levels in the generation of delayed peaks (and its timing) has been explored, including catchments in Japan, central Europe, UK, USA, as well as Africa and New Zealand. The reader should be better informed about what is already known and why the presented work in needed. The reader could understand from the introduction that the mechanisms and thresholds have not been previously investigated. For instance, I disagree with the statement in lines 65-66.
I also had some problems to understand some of the methods. The XEW is a relatively small catchment (4.22 km2) with quick reaction times (e.g. Figure 11), why did you average the 5-min data (e.g. discharge) or 10-min data (soil water content) to hourly values? I assume by smoothing the data you might be losing significant information when looking at reaction times (which is a significant part of the presented work). Did you check that out? Did you loose two years of discharge data due to environmental challenges? Maybe there was another reason for this.
Soil water content probes were installed at two sites: “five sensors installed in Hillslope 1 and three near WS900 at 80 cm depth intervals”. At which depths? Installing them at “80 cm depth intervals” seems impossible if soils are 1.5 m depth. How were probes installed? Which was the data variability? How and why were the locations chosen and how do they represent what is happening in the catchment? Data was “aggregated to hourly intervals, and the arithmetic mean SWC across the profiles was used for analysis”. Why wasn’t the response of different layers investigated? This seems a lot of averaging to me and we have no clue of data variability across the 8 sites.
I also would like to have more information about how the groundwater data has been treated. The authors mention that the data of each well has been normalised using the Detty and McGuire (2010) method to normalise groundwater levels using an index (IG) calculated for each borehole. To my understanding Detty and McGuire did not use any index for normalisation: “For each well and event, we calculated the median height of the water table above the lowest recordable depth of each instrument and normalized that value to the total range of heights observed throughout the study period at each well (0 D minimum observed height or lowest recordable depth, 1 D maximum observed height, referred to hereafter as ‘normalized’).” I am not sure you are referring to this. Why were different hillslopes instrumented? Which is the logic behind the location of the equipment. The authors then calculated the arithmetic mean of the index to represent the overall groundwater level in the watershed. It is very difficult to address the implications of this as we do not know how the data looks like (I understand all plots show average data), but averaging data from all wells where there is water is a very simplistic approach and the authors should provide evidence that it is not.
The authors conclude that “delayed stormflow is initiated when soil water content reaches field capacity”. However, if I am not mistaken, there is no prediction of field capacity in the manuscript. This leads me to conclude that one of the ‘key poitns’ of the paper is not supported by data. I agree that the concept of field capacity, by definition, is not a static physical soil property. It also varies with depth. It can be determined in many ways, but it would have appreciated to have seen this addressed.
The authors selected events using an algorithm described by Tian et al (2012) – maybe a bit more information could be given. Separation seems to be exclusively based on rainfall patterns. My experience is that this type of algorithms can detect first peaks, but that they are not suited to investigate delayed flows. This because after a given event, other events can happen while baseflow is rising or falling (what would be delayed flow). I understanding that the authors identified 14 events when after an event there was not other events, resulting in nicely drawn delayed peaks. I do not see a problem with this, but there is no explanation about how the single events have been separated from the events with delayed peaks, what poses a fundamental problem for me to understand what has been done. Also, while reading the paper I kept wondering how the events would look like. I really miss hydrological data in the paper – as all the figures show processed/averaged data, or schematic figures (e.g. figures 6 and 7). I saw afterwards that there is an Appendix. This could have been mentioned (was it?).
The HYSEP program is used to separate baseflow from stormflow, with “manual verification and adjustment based on straight line separation methods”. Do you mean the constant slope method of Hewlett and Hibbert (1967)? I am not sure this data is used in the catchment and how does it compare to the tracer-based hydrograph separation carried out in Cui et al (2024). When you refer to event’s stormflow along the manuscript, do you refer to the discharge minus baseflow? This should be clarified.
The authors define thresholds in a very arbitrary way. For instance, the 0.20 threshold described in Figure 5 (lines 207-2012). Is this only a visual exploration? Was there a statistical way to define this threshold?
The structure of the manuscript is puzzling. There are three sections in the results, which include discussion and comparison with the literature (what should be moved to the discussion section). On the other hand, new results are presented in the discussion section.
Too little is said about the thick regolith, I think more information is needed here and it what would be very useful to understand the behaviour of the catchment. For instance, soils are described as “brown earth and cinnamon types”. A bit more information would be appreciated here. Also, at some point the authors argue that different groundwater dynamics in different hillslopes are due to specific hillslope’s geological structures. This should be further explored in the discussion (not the results section).
MINOR COMMENTS
- Line 29: not clear what you mean by ‘expands vertically’.
- Line 39: the catchment is 4.22 km2: what do you mean by flooding? I would use another term.
- Line 68: this sentence repeats the same as line 57.
- Line 69-70: give some examples of studies where they fail to do so and the reasons. I am not sure I agree with this.
- Line 75: the authors
- Line 76: low.
- Line 76-78: It is stated that analysis of 15 bi modal events collected during a decade have already been analysed and contributed to the advancement of runoff generation studies. Maybe it would be nice to summaries this in the introduction. Or do you refer to the work presented in the manuscript?
- Line 103: I would indicate there are 5 stations also here in text.
- Line 112: data covering two complete years?
- Line 112: data was lost during 2 years because of ‘environmental reasons’? This is not clear.
- Line 117: why did you aggregate the data?
- Line 127: I think the approach should be shortly described here.
- Line 188: “among these” reads confusing as you are not refering to the previous sentence.
- Line 226-228: I think this is rather an opinion and should be discussed in the discussion section.
- Lines 251-252: I would remove as a summary of previous section should not be needed.
- Line 286: why HS3 compared to HS1 and HS2.
- Line 295: replacing c?
- Figure 1. The exact same figure is used in Che et al. (2024, HESS). I wonder if this allowed without referring t the first figure published. It is difficult to see the location of the weather stations. Where are the five soil water profiles located? Are this indicated as “research hillslopes”? or what are research hillslopes? The authors refer to Hillslope 1 in line 116 - but not to the others. An explanation is missing.
- Lines 31-33. The authors conclude that their fundings “enhance our understanding of delayed stormflow generation in similar regions”. I think it would be nice to better explain this. Where? Why?
- I understand section 3.3 refers to the 14 selected events, is that right?
- Figure 8. It would be nice to have a little map displaying the location of the wells.
- Figure 9 is nice but difficult to understand with the little information we have about the catchment.
- Figure 10: I understand there are two points per event in that graph. Would be nice to know which points refer to Ts1-ts3 and which to ts2-ts3. I wonder if it is correct to use these two points per event to draw a regression line. The x axis indicates that there is 10 days difference between the reaction in one well and another. I do not understand this and I think the paper do not provide enough evidence to the reader to show what is going on. Why the others wells were not included in the analysis?
Citation: https://doi.org/10.5194/egusphere-2024-2177-RC2 -
AC2: 'Reply on RC2', Zhen Cui, 29 Nov 2024
Comment 1:
This manuscript examines the runoff generation processes leading to delayed peaks and proposes a conceptual model for the Xitaizi Experimental Watershed (XEW), North China. Overall, this paper could have the potential to contribute to the literature, but I think improvements in the way of presenting the research questions, the results and discussion would help to highlight the unique aspects of this work.
Response 1:
Thank you for your valuable feedback. We are pleased that you recognize the potential contribution of this study to the literature. We also appreciate your suggestions for improving the way research questions, results, and discussion are presented to better highlight the unique aspects of this work.
In response to your comments, we will make the following revisions:
- Research Questions: We will restructure the introduction to present the research questions more clearly and concisely, explicitly linking them to the challenges observed in runoff generation processes and delayed peaks in the Xitaizi Experimental Watershed (XEW).
- Results: We will improve the organization and interpretation of the results section, ensuring that key findings are clearly highlighted and directly address the research questions. This includes a more focused presentation of the conceptual model and its implications.
- Discussion: We will enhance the discussion section by providing a deeper interpretation of the results, comparing our findings with existing literature, and highlighting the unique contributions of this study to understanding delayed runoff peaks and their mechanisms.
Comment 2:
In my opinion, the manuscript is strongly linked to Cui et al (2024), which has recently been published in HESS and addresses the “characteristics and occurrence” of bi-modal events in the same catchment (https://doi.org/10.5194/hess-28-3613-2024). This is a personal opinion, but I do not understand the strategy of publishing two independent papers instead of summarising key results in one. I understand the same dataset has been used in both and methods descriptions are very similar (or the same). The authors mention that the data will be made available in Zenodo at the time of publication. Does this mean that the data is different than https://zenodo.org/records/12581739? If yes, it would have been nice to make the data available.
Response 2:
Thank you for your valuable feedback and for pointing out the connection between this manuscript and our previously published study (Cui et al., 2024, HESS). We greatly appreciate your perspective and would like to clarify the rationale for separating the work into two papers.
The HESS paper focuses on the characteristics and occurrence conditions of bimodal hydrographs, analyzing the runoff processes, source composition, and conditions for bimodal responses using hydrometric and isotope data. In contrast, the current manuscript delves into the underlying mechanisms of bimodal responses, which are crucial for understanding this phenomenon and improving runoff prediction models.
While we initially considered combining all results into a single paper, we realized that doing so would make the manuscript overly lengthy and dilute the focus on either the phenomenon's characteristics or its mechanisms. Based on feedback from literature reviews and discussions with other researchers, we determined that separating these studies would allow for a more detailed and focused presentation of the results, better serving the hydrological community. To ensure clarity, we will explicitly articulate the unique focus of each study in the introduction, emphasizing their complementary nature and avoiding any perception of redundancy.
Regarding the dataset, the data used in this manuscript are consistent with those shared in Zenodo (https://zenodo.org/records/12581739). However, this study includes more detailed analyses of soil moisture and groundwater level data. If needed, we are willing to upload the finer-resolution soil moisture data for specific observation points to Zenodo after this manuscript is accepted, ensuring transparency and reproducibility of our research.
Comment 3:
I think the introduction could present better the significant amount of literature where the role of soil water content and groundwater levels in the generation of delayed peaks (and its timing) has been explored, including catchments in Japan, central Europe, UK, USA, as well as Africa and New Zealand. The reader should be better informed about what is already known and why the presented work in needed. The reader could understand from the introduction that the mechanisms and thresholds have not been previously investigated. For instance, I disagree with the statement in lines 65-66.
Response 3:
Thank you for your insightful comment. We appreciate your suggestion to provide a more comprehensive overview of existing literature on the role of soil water content and groundwater levels in generating delayed peaks. In response, we will expand the introduction to include studies from various regions, including Japan, central Europe, the UK, the USA, Africa, and New Zealand, that have explored these processes. Specifically, we will add references to studies such as Detty and McGuire (2010), Farrick and Branfireun (2014), and Penna et al. (2011), highlighting their findings on thresholds and mechanisms driving delayed peaks.
Additionally, we acknowledge that the statement in Lines 65-66 was overly broad and could be misinterpreted. We will revise this sentence to more accurately reflect the specific gaps in the existing literature, particularly regarding the mechanisms and post-threshold runoff processes in bimodal hydrographs.
Comment 4:
I also had some problems to understand some of the methods. The XEW is a relatively small catchment (4.22 km2) with quick reaction times (e.g. Figure 11), why did you average the 5-min data (e.g. discharge) or 10-min data (soil water content) to hourly values? I assume by smoothing the data you might be losing significant information when looking at reaction times (which is a significant part of the presented work). Did you check that out? Did you loose two years of discharge data due to environmental challenges? Maybe there was another reason for this.
Response 4:
Thank you for your thoughtful comment regarding the data processing and its potential impact on the analysis. We appreciate the opportunity to clarify our approach to aggregating data and addressing data loss.
- Data aggregation and resolution
We chose to aggregate the 5-minute discharge data and 10-minute soil water content (SWC) data to hourly intervals to maintain consistency with the groundwater level data, which were recorded at an hourly frequency. This decision ensures that the relationships between these variables can be analyzed uniformly without introducing temporal inconsistencies.
Additionally, our study focuses on the second runoff peak, which typically has a delayed response time ranging from 5 hours to several days. Given the relatively slow dynamics of this process, we determined that lowering the data resolution to hourly intervals would have a negligible impact on the analysis of the timing and magnitude of the delayed peak.
For processes with shorter response times, such as the first runoff peak, we conducted separate analyses using higher-resolution (10-minute) discharge data in our previous study (Cui et al., 2024). This ensures that processes with faster dynamics were analyzed with appropriate temporal resolution.
- Validation of aggregation effects
To ensure that the aggregation did not compromise the results, we conducted a sensitivity analysis comparing the timing and magnitude of key events using both the original and aggregated data. The results confirmed that the hourly data adequately captured the dynamics of the delayed runoff peak, with minimal differences from the higher-resolution data.
- Data loss
Regarding the missing discharge data from 2018 to 2019, the primary cause was environmental challenges, including equipment malfunctions and extreme weather conditions. While this resulted in the exclusion of certain events from our analysis, the remaining dataset provided sufficient coverage (95 events) to support robust conclusions.
In the revised introduction, we will add the following content:
“Due to environmental challenges such as sensor malfunctions during extreme weather events, discharge data for some periods were unavailable, including stormflow data from July 19 to August 16, 2016, and all data from 2018 to 2019. While these losses resulted in the exclusion of certain events, the remaining dataset (95 events) provided sufficient representation of bimodal hydrographs to support robust analyses.”
“To ensure consistency across datasets, the 5-minute discharge data and 10-minute SWC data were aggregated to hourly intervals, matching the groundwater level data. Preliminary analysis showed that the delayed second streamflow peak has a response time well above the hourly scale, ranging from 5 hours to several days (Cui et al., 2024). Thus, we consider the potential information loss due to this aggregation to be negligible for the purposes of this study. Higher-resolution data were retained for separate analyses involving faster processes, such as the first streamflow peak, in previous studies.”
We hope this explanation addresses your concerns. Thank you again for highlighting these important points, which allowed us to provide a more comprehensive account of our methodology.
Comment 5:
Soil water content probes were installed at two sites: “five sensors installed in Hillslope 1 and three near WS900 at 80 cm depth intervals”. At which depths? Installing them at “80 cm depth intervals” seems impossible if soils are 1.5 m depth. How were probes installed? Which was the data variability? How and why were the locations chosen and how do they represent what is happening in the catchment? Data was “aggregated to hourly intervals, and the arithmetic mean SWC across the profiles was used for analysis”. Why wasn’t the response of different layers investigated? This seems a lot of averaging to me and we have no clue of data variability across the 8 sites.
Response 5:
Thank you for your insightful comments and for highlighting the importance of providing more details regarding the installation and analysis of soil water content (SWC) probes. We appreciate the opportunity to clarify these aspects and address your concerns.
The SWC probes were installed at eight locations across the watershed: five along Hillslope 1 and three near WS1000. At each location, probes were installed at 10 cm intervals from the surface to a depth of 80 cm, providing measurements at depths of 10, 20, 30, 40, 50, 60, 70, and 80 cm. The reference to “80 cm depth intervals” was an error in phrasing, and we will correct this to accurately describe the installation methodology.
Additionally, we would like to clarify that the correct location near the meteorological station is WS1000. The mention of WS900 in the original manuscript was incorrect, and we sincerely apologize for this mistake. This has been corrected in the revised manuscript to ensure accuracy and prevent any misunderstanding.
The selection of these observation sites was based on extensive field surveys considering slope orientation, gradient, and vegetation cover to ensure that they are representative of the catchment’s hydrological characteristics. As shown in Figure 1, the locations span a significant portion of the watershed, from Hillslope 1 to WS1000, covering diverse topographical and vegetation conditions. We believe the arithmetic mean of SWC across these eight profiles effectively represents the overall soil moisture status and variability in the catchment.
During preliminary analysis, we observed that the time series of SWC at different locations and depths showed highly consistent trends, with only minor differences in magnitude. This consistency suggested that using the average SWC across the profiles was appropriate for analyzing the relationship between soil water storage and groundwater dynamics. Given that the focus of this study is on the total soil water storage (0–80 cm depth) and its influence on groundwater levels, we did not analyze the responses of individual soil layers. We acknowledge that such an analysis could provide additional insights and will consider it for future work.
Thank you again for raising these important points, which have allowed us to improve the clarity and rigor of our methods section. We hope this explanation addresses your concerns.
Comment 6:
I also would like to have more information about how the groundwater data has been treated. The authors mention that the data of each well has been normalised using the Detty and McGuire (2010) method to normalise groundwater levels using an index (IG) calculated for each borehole. To my understanding Detty and McGuire did not use any index for normalisation: “For each well and event, we calculated the median height of the water table above the lowest recordable depth of each instrument and normalized that value to the total range of heights observed throughout the study period at each well (0 D minimum observed height or lowest recordable depth, 1 D maximum observed height, referred to hereafter as ‘normalized’).” I am not sure you are referring to this. Why were different hillslopes instrumented? Which is the logic behind the location of the equipment. The authors then calculated the arithmetic mean of the index to represent the overall groundwater level in the watershed. It is very difficult to address the implications of this as we do not know how the data looks like (I understand all plots show average data), but averaging data from all wells where there is water is a very simplistic approach and the authors should provide evidence that it is not.
Response 6:
Thank you for your insightful comments and for highlighting the need for further clarification regarding the treatment of groundwater data and the rationale behind instrumentation placement. Below, we address the concerns raised:
- Groundwater normalization and the use of IG
We acknowledge that the explanation of our groundwater level normalization and the use of the index (IG) in the manuscript could have been clearer. The majority of our analyses in the manuscript are based on actual groundwater levels observed at individual wells. However, in discussions of overall watershed-scale groundwater dynamics, we normalized groundwater levels at each well to account for differences in water table depth and range across locations. This normalization process involved scaling observed groundwater levels at each borehole relative to their respective ranges throughout the study period (minimum to maximum observed groundwater levels).
To facilitate analysis at the watershed scale, the arithmetic mean of normalized values across all wells was calculated and referred to as IG (index for groundwater level). While Detty and McGuire (2010) similarly normalized groundwater heights, their work did not define an index equivalent to IG. Our choice to refer to the averaged normalized groundwater levels as IG was for convenience in this study. We will revise the manuscript to clarify this distinction and remove the citation of Detty and McGuire (2010) where it is inappropriate. Instead, we will explicitly describe the steps used for normalization in our study. The revised text now reads:
“Groundwater levels were normalized following the method described by Detty and McGuire (2010). For each well and event, the median height of the water table above the lowest recordable depth of the instrument was calculated and normalized to the total observed range, where 0 represents the minimum height and 1 represents the maximum height. This normalized value was referred to as the groundwater index (IG). We used IG to facilitate comparisons across wells with different absolute GWL ranges and to represent the overall GWL dynamics in the watershed.”
- Logic behind instrumentation placement
The hillslopes instrumented in this study were selected following extensive field surveys that considered factors such as slope orientation, gradient, vegetation cover, and proximity to stream channels. These factors were deemed representative of the catchment's hydrological and geological conditions. The selected hillslopes represent typical topographic and hydrological conditions of the catchment and ensure adequate coverage of spatial variability. These choices allowed us to investigate spatial variability in GWL responses across hillslopes with contrasting hydrological and geological characteristics. The following text will be added in the Materials and methods section in the revised manuscript:
“Instrumentation across three hillslopes (HS1, HS2, and HS3) was designed to capture the spatial variability of soil moisture and groundwater dynamics under different topographic and geological conditions. SWC probes and boreholes were strategically located along topographical gradients (e.g., hilltop, mid-slope, and foot slope) to reflect potential variability in SWC and GWL responses. This setup enabled us to investigate the influence of hillslope-specific characteristics on GWL dynamics and their relationship with SWC. The spatial distribution of boreholes is shown in Fig. 1.”
- Simplistic averaging Concern
We understand your concern about the simplistic approach of averaging normalized groundwater levels (IG) across wells. As mentioned earlier, most of our analyses are based on data from individual wells. The use of IG is limited to specific discussions where a general representation of watershed-scale groundwater behavior is necessary. In addition, this approach was informed by previous analyses in our earlier work (Cui et al., 2024). In that study, we compared IG values across wells and found consistent temporal trends in groundwater dynamics, despite spatial variations in absolute levels and lag times. The strong correlation between IG values at different locations suggests that the averaged IG effectively represents the overall groundwater dynamics within the watershed. This consistency validates the use of the arithmetic mean as a practical and reliable indicator for watershed-scale groundwater responses.
Comment 7:
The authors conclude that “delayed stormflow is initiated when soil water content reaches field capacity”. However, if I am not mistaken, there is no prediction of field capacity in the manuscript. This leads me to conclude that one of the ‘key poitns’ of the paper is not supported by data. I agree that the concept of field capacity, by definition, is not a static physical soil property. It also varies with depth. It can be determined in many ways, but it would have appreciated to have seen this addressed.
Response 7:
Thank you for your valuable comment regarding the use of field capacity in the manuscript. We appreciate your insight and agree that the concept of field capacity is complex, varying with depth and not being a static physical property.
In this study, we observed that during storm events, soil water content (SWC) increased to a specific high value (approximately 0.24 volumetric water content) before stabilizing and then declining, even when rainfall had not yet ceased. Based on this consistent behavior across all monitored sites, we interpreted this threshold as representing the soil's maximum water-holding capacity, which we approximated as the field capacity. We recognize that this is an indirect approach and that field capacity was not directly measured due to the challenges of field monitoring in the experimental watershed.
Furthermore, given the relatively small variability in the average SWC across monitoring sites and the substantial variability in soil depth within the watershed, we chose to analyze SWC as a direct indicator of soil water-holding capacity rather than converting it to water storage (in mm). This approach simplifies the analysis while still capturing the essential dynamics of soil water behavior.
We acknowledge this approximation introduces limitations, particularly in representing the spatial variability of field capacity. We will clarify this assumption in the revised manuscript and include a discussion of its implications in the limitations section. Additionally, we will emphasize in the text that this study identifies a stable SWC threshold (interpreted as field capacity) at which delayed stormflow is initiated. Future studies could focus on directly measuring or modeling field capacity to validate and refine these findings.
Thank you again for your thoughtful feedback, which has helped us improve the clarity and rigor of our manuscript.
Comment 8:
The authors selected events using an algorithm described by Tian et al (2012) – maybe a bit more information could be given. Separation seems to be exclusively based on rainfall patterns. My experience is that this type of algorithms can detect first peaks, but that they are not suited to investigate delayed flows. This because after a given event, other events can happen while baseflow is rising or falling (what would be delayed flow). I understanding that the authors identified 14 events when after an event there was not other events, resulting in nicely drawn delayed peaks. I do not see a problem with this, but there is no explanation about how the single events have been separated from the events with delayed peaks, what poses a fundamental problem for me to understand what has been done. Also, while reading the paper I kept wondering how the events would look like. I really miss hydrological data in the paper – as all the figures show processed/averaged data, or schematic figures (e.g. figures 6 and 7). I saw afterwards that there is an Appendix. This could have been mentioned (was it?).
Response 8:
Thank you for your comment and for raising concerns about the event selection process and the representation of hydrological data. We acknowledge the need to provide additional clarification and address the specific points you raised.
- Event selection algorithm:
In this study, we employed the algorithm proposed by Tian et al. (2012) to identify rainfall events. This method effectively separates individual rainfall events under typical conditions. However, as you noted, such algorithms primarily focus on detecting rainfall patterns and do not inherently account for delayed flows or overlapping events.
To address this, we performed an additional manual step to identify delayed stormflow events based on their distinct hydrograph characteristics (as described in Cui et al., 2024). These events are rare but visually distinguishable by the presence of an arch-shaped delayed peak, separated from the direct peak. We will revise the "Separation of Rainfall-Runoff Events" section to provide more detail about our identification process.
- Representation of hydrological data:
We appreciate your insightful comment regarding the inclusion of raw hydrological data (e.g., hydrographs and rainfall patterns for eight selected events) in the Appendix, which was not explicitly referenced in the main text. To address this, we will revise the manuscript to include a clear reference to the Appendix in Introduction of the main text.
Comment 9:
The HYSEP program is used to separate baseflow from stormflow, with “manual verification and adjustment based on straight line separation methods”. Do you mean the constant slope method of Hewlett and Hibbert (1967)? I am not sure this data is used in the catchment and how does it compare to the tracer-based hydrograph separation carried out in Cui et al (2024). When you refer to event’s stormflow along the manuscript, do you refer to the discharge minus baseflow? This should be clarified.
Response 9:
Thank you for pointing out the need for additional clarity regarding the hydrograph separation methods and the definition of stormflow. You are correct that we used the constant slope method described by Hewlett and Hibbert (1967), implemented via the HYSEP program (Sloto & Crouse, 1996). Automated results were manually verified and adjusted to improve accuracy. We will clarify in the methods section that "event stormflow" refers to the discharge minus baseflow as calculated by the straight-line separation method.
Regarding the comparison with Cui et al. (2024), that study utilized both the straight-line separation and tracer-based hydrograph separation methods due to its focus on water source partitioning and bimodal hydrograph characteristics. In contrast, the current study focuses on the overall dynamics and thresholds of delayed stormflow. We will revise the manuscript to emphasize this methodological distinction and its relevance to the study objectives. Thank you again for highlighting this, as it allowed us to enhance the manuscript's clarity and rigor.
Comment 10:
The authors define thresholds in a very arbitrary way. For instance, the 0.20 threshold described in Figure 5 (lines 207-212). Is this only a visual exploration? Was there a statistical way to define this threshold?
Response 10:
Thank you for your insightful comment regarding the definition of thresholds, particularly the 0.20 threshold described in Figure 5. We appreciate your concern about ensuring the robustness and scientific rigor of these thresholds.
In the current study, the 0.20 threshold was initially identified through visual exploration of Figure 5, where the SWC dynamics from 14 distinct rainfall-runoff events showed consistent stabilization around this value. However, we acknowledge that a more statistically rigorous method would strengthen the validity of this threshold. To address this, we will perform an additional analysis using descriptive statistical methods to verify the stable SWC values across 14 storm events. We will revise the manuscript to incorporate these results and provide a more robust explanation of the threshold determination process.
Thank you for highlighting this critical aspect, which has helped improve the rigor of our study.
Comment 11:
The structure of the manuscript is puzzling. There are three sections in the results, which include discussion and comparison with the literature (what should be moved to the discussion section). On the other hand, new results are presented in the discussion section.
Response 11:
Thank you for your valuable feedback regarding the structure of the manuscript. We understand your concern about the inclusion of discussion and comparison with the literature in the results section, as well as the presentation of new results in the discussion section. We appreciate your suggestion to clearly separate these elements to improve the manuscript's organization and clarity.
To address this issue, we will restructure the manuscript as follows:
The results section will focus exclusively on presenting the findings of this study, without introducing comparisons with the literature or interpretative discussions.
Content involving comparisons with the literature and interpretations of the findings will be relocated to the discussion section, ensuring it focuses on contextualizing our results within the broader field.
Any new results currently presented in the discussion section will be moved to the results section, maintaining a clear distinction between results and interpretation.
Comment 12:
Too little is said about the thick regolith, I think more information is needed here and it what would be very useful to understand the behaviour of the catchment. For instance, soils are described as “brown earth and cinnamon types”. A bit more information would be appreciated here. Also, at some point the authors argue that different groundwater dynamics in different hillslopes are due to specific hillslope’s geological structures. This should be further explored in the discussion (not the results section).
Response 12:
Thank you for raising this important point. We acknowledge that the description of the thick regolith and its implications for hydrological behavior in the Xitaizi Experimental Watershed (XEW) could be expanded. The characteristics of the regolith, including soil depth, type, and underlying bedrock properties, are indeed critical for understanding the catchment's groundwater dynamics and delayed stormflow processes.
To address this, we will add more detailed information on the regolith and geological structures in the study site description, highlighting its influence on hydrological behavior. Specifically:
- Underlying bedrock: We will include a more detailed account of the granite bedrock’s weathering profile and fracturing, and how these geological characteristics vary among the three experimental hillslopes.
- Hydrological implications: In the discussion section, we will further explore how differences in geological structures among hillslopes influence groundwater dynamics and delayed streamflow.
MINOR COMMENTS
Comment 13:
Line 29: not clear what you mean by ‘expands vertically’.
Response 13:
Thank you for your comment regarding the phrase "expands vertically." We appreciate your suggestion to clarify this statement. Upon review, we recognize that the original phrasing may not have been sufficiently clear. To address this, we will revise the sentence as follows:
"Simultaneously, the effective connection area between the stream channel and adjacent hillslopes increases in the vertical dimension."
Comment 14:
Line 39: the catchment is 4.22 km2: what do you mean by flooding? I would use another term.
Response 14:
Thank you for your comment. We appreciate your suggestion to reconsider the use of the term “flooding” given the size of the Xitaizi Experimental Watershed (4.22 km²). The term “flooding” was intended to describe localized inundation or temporary water pooling within certain areas of the catchment during storm events, rather than large-scale flood events. To avoid any potential misunderstanding, we will revise the sentence to use a more precise term.
Comment 15:
Line 68: this sentence repeats the same as line 57.
Response 15:
Thank you for your valuable feedback regarding the repetition between Line 57 and Line 68. We appreciate your attention to detail and agree that reducing redundancy can improve the clarity and flow of the manuscript.
After careful consideration, we will retain the sentence in Line 57, as it provides a concise introduction to the significance of bimodal hydrographs within the context of nonlinear runoff responses. And we will revise Line 68 to focus on the unique aspects of bimodal runoff processes, while retaining the core emphasis on their nonlinear characteristics.
Comment 16:
Line 69-70: give some examples of studies where they fail to do so and the reasons. I am not sure I agree with this.
Response 16:
Thank you for your valuable feedback. We appreciate your suggestion to provide specific examples to support the statement that many studies fail to distinguish between unimodal and bimodal streamflow responses. In response, we will revise the paragraph to include examples from the literature and explain the reasons behind this limitation.
Comment 17:
Line 75: the authors
Response 17:
Thank you for your insightful comment and suggestion. We understand your suggestion to adjust the phrasing, such as replacing "our" with "the authors," to enhance the objectivity of the text. In the course of revising the manuscript, we will remove this sentence to streamline the introduction and maintain a more neutral tone.
Comment 18:
Line 76: low.
Response 18:
Thank you for your correction. We understand that using "lower" could imply a comparison without a clear reference, which may lead to ambiguity. To address this, we will revise the sentence to use "low" instead, ensuring greater clarity and accuracy.
Comment 19:
Line 76-78: It is stated that analysis of 15 bi modal events collected during a decade have already been analysed and contributed to the advancement of runoff generation studies. Maybe it would be nice to summaries this in the introduction. Or do you refer to the work presented in the manuscript?
Response 19:
Thank you for your valuable comment. We appreciate your suggestion to clarify the relationship between the analysis of 15 bimodal events mentioned in Lines 76–78 and the work presented in this manuscript.
The 15 bimodal events collected over the past decade were primarily analyzed in our previously published paper (Cui et al., 2024), which focused on identifying the characteristics and occurrence conditions of bimodal and unimodal runoff responses. This manuscript builds on that foundation by exploring the intrinsic mechanisms driving the threshold behavior observed in bimodal hydrograph processes.
To enhance clarity and eliminate redundancy, we will revise both the first and last paragraphs of the introduction. The updated text now includes a concise summary of the key findings from the 2024 paper and elaborates on the complementary relationship between the two studies, providing a more comprehensive context for the present research.
Comment 20:
Line 103: I would indicate there are 5 stations also here in text.
Response 20:
Thank you for your valuable comment. We would like to clarify that there are four meteorological stations in the Xitaizi Experimental Watershed (XEW), located at elevations of 700 m, 900 m, 1000 m, and 1100 m, as shown in Fig. 1. These stations are named WS700, WS900, WS1000, and WS1100, respectively. The text in Line 103 correctly refers to four stations, and we will carefully review the manuscript to ensure consistency in this description throughout the paper.
Comment 21:
Line 112: data covering two complete years?
Response 21:
Thank you for your comment. We appreciate your concern about the data coverage and its impact on our analysis. We would like to clarify the reasons behind the exclusion of data from 2018 and 2019, as well as stormflow data from July 19 to August 16, 2016.
During the July–August 2016 period, high water levels inundated the Parshall flume, causing the HOBO logger to record inaccurately low discharge values for two bimodal events. While the general hydrograph shapes and trends remained reliable, these two events were excluded from the discharge analysis to ensure data accuracy. However, associated soil moisture and groundwater level data were unaffected and retained for other analyses.
For 2018 and 2019, rainfall was relatively low overall, and unfortunately, sensor malfunctions during major rainfall events resulted in the loss of critical discharge data. Given the study’s focus on stormflow hydrographs during heavy rainfall events, we excluded these two years entirely from the analysis.
Despite these exclusions, the remaining dataset, comprising 95 events, provides a robust representation of bimodal hydrograph patterns. This ensures that the analysis remains comprehensive and reliable. We hope this explanation addresses your concerns and clarifies the rationale for data handling decisions. Thank you again for raising this important point.
To address your concern, we will ensure that the revised text in Lines 110–112 explicitly states the reasons for data exclusion and highlights the representativeness of the retained dataset. The updated sentence reads:
" Due to challenges such as sensor malfunctions, discharge data for some periods were unavailable. Specifically, during July 19 to August 16, 2016, high water levels inundated the flume, leading to inaccurately low discharge values for two bimodal events, which were excluded from discharge analysis. Additionally, sensor malfunctions in 2018 and 2019 resulted in the loss of critical discharge data during major rainfall events, leading to the exclusion of these two years. Despite these exclusions, the remaining dataset, comprising 95 events, provided sufficient representation of bimodal hydrograph patterns to support robust and reliable analyses."
Comment 22:
Line 112: data was lost during 2 years because of ‘environmental reasons’? This is not clear.
Response 22:
Thank you for your comment. We agree that the original description of "environmental reasons" lacked specificity and could cause confusion. In response to a related comment (Comment 21), we will revise the relevant section to provide a clearer explanation of the data loss.
Comment 23:
Line 117: why did you aggregate the data?
Response 23:
Thank you for your comment regarding Line 117 and the rationale for aggregating the data. To address this concern, we will revise the methods section to include a detailed explanation of the aggregation process and its justification.
Comment 24:
Line 127: I think the approach should be shortly described here.
Response 24:
Thank you for your suggestion to provide a brief description of the approach used to calculate the groundwater index (IG). We agree that adding this information will enhance the clarity and transparency of the methods section.
In response, we will revise Line 127 to include a brief description of the approach by Detty and McGuire (2010).
Comment 25:
Line 188: “among these” reads confusing as you are not refering to the previous sentence.
Response 25:
Thank you for pointing out the potential confusion caused by the phrasing of "among these" in this sentence. We acknowledge that the reference could be clearer to avoid ambiguity. To address this, we will revise the sentence to explicitly refer to the relevant context, ensuring that readers can follow the logical flow without confusion.
Comment 26:
Line 226-228: I think this is rather an opinion and should be discussed in the discussion section.
Response 26:
Thank you for pointing out that the statement in Lines 226–228 could be interpreted as an opinion rather than a direct result of the data analysis. We agree with your assessment and will revise the manuscript accordingly. Specifically, we will move the sentence “These response patterns suggest that the GWL dynamics are not only influenced by SWC but are also dependent on the specific hillslope’s geological structure.” to the Discussion section, where it is further elaborated upon in the context of other results and supported by additional references. This adjustment ensures that the Results section is focused on presenting the data and associated observations, while broader interpretations and implications are discussed in the appropriate section.
Comment 27:
Lines 251-252: I would remove as a summary of previous section should not be needed.
Response 27:
Thank you for your suggestion. We agree that summarizing the findings of the previous section within the first sentence of Section 3.4 could be redundant. To address this, we will remove the sentence "Figure 8 reveals that while the magnitude of GWL increments across various locations remains relatively consistent, the lag time for GWL to reach its maximum value exhibits substantial variation."
Instead, we will revise the introductory part of Section 3.4 to directly introduce the analysis and focus of the section, avoiding repetition of the results already presented in Section 3.3.
Comment 28:
Line 286: why HS3 compared to HS1 and HS2.
Response 28:
Thank you for your comment and for seeking clarification regarding why Hillslope 3 (HS3) was compared to Hillslope 1 (HS1) and Hillslope 2 (HS2). We appreciate the opportunity to elaborate on this point and provide additional context to ensure clarity.
Hillslope 3 (HS3) was chosen as a point of comparison because it exhibited the slowest groundwater level (GWL) response among the three hillslopes analyzed. As shown in Figure 8, the lag times for GWL to reach its maximum value at HS3 (e.g., 0.4 to 11.7 days at W31 and 0.8 to 8.1 days at W32) were substantially longer than those at HS1 and HS2. This unique characteristic makes HS3 a useful reference for understanding the relative differences in GWL dynamics across the hillslopes.
Moreover, as described in Cui et al. (2024, HESS), the GWL response times at different observation points were found to be highly correlated with the timing of delayed stormflow. Consequently, comparing the GWL dynamics of HS1 and HS2 to those of HS3 allows us to explore potential links between hillslope geological structures and delayed stormflow generation. This approach also provides insights into how variations in hillslope geology, soil properties, and hydrological processes influence the timing and magnitude of GWL responses.
To ensure this rationale is clear to readers, we will add the following clarification to Section 3.3:
“The analysis revealed that Hillslope 3 (HS3) exhibited the slowest GWL responses, with longer lag times compared to Hillslope 1 (HS1) and Hillslope 2 (HS2) (Fig. 8). This distinction makes HS3 an important reference for analyzing differences in GWL dynamics across hillslopes. Previous findings from Cui et al. (2024) have shown that GWL response times are closely correlated with delayed stormflow timing, highlighting the importance of understanding these dynamics. By comparing the GWL response times of HS1 and HS2 to those of HS3, we aim to identify the potential roles of hillslope geological structures and soil water content (SWC) thresholds in influencing delayed stormflow generation.”
Comment 29:
Line 295: replacing c?
Response 29:
Thank you for pointing out the potential confusion caused by the phrasing. Upon review, we recognize that the term “replacing c” is unclear and might have led to misunderstandings. This was an oversight during the writing process, and we apologize for the confusion. The intended meaning is that replacing the vertical axis variable, currently labeled as IG, with the GWL at any specific location would yield a similar pattern, albeit with variations in GWL thresholds across different sites. To clarify this, we will revise the sentence as follows:
"A similar pattern emerges when replacing the vertical axis variable with GWL at any specific location, though the GWL thresholds vary across different sites."
Comment 30:
Figure 1. The exact same figure is used in Che et al. (2024, HESS). I wonder if this allowed without referring t the first figure published. It is difficult to see the location of the weather stations. Where are the five soil water profiles located? Are this indicated as “research hillslopes”? or what are research hillslopes? The authors refer to Hillslope 1 in line 116 - but not to the others. An explanation is missing.
Response 30:
We appreciate the reviewer’s concerns regarding the reuse of the figure and the clarity of the figure presentation. To address these points, we will make the following revisions:
- Redrawing of Figure 1:
We will redraw Figure 1 to provide a clearer and more readable representation of the elevation and equipment distribution in the experimental watershed. We will enlarge the markers and labels to clearly mark the locations of the weather stations, soil moisture observation profiles, groundwater observation wells, and the three experimental hillslopes. Additionally, we will add a brief description of the borehole cores.
- Clarify the role of weather stations in Section 2.2:
"Meteorological data were collected from 2013 to 2023 using four GRWS100 automatic weather stations, named WS700, WS900, WS1000, and WS1100, based on their elevations of 700 m, 900 m, 1000 m, and 1100 m, respectively, and strategically distributed along an elevation gradient within XEW."
- Explanation of research hillslopes:
The research hillslopes (Hillslope 1, Hillslope 2, and Hillslope 3) were used as key areas to analyze the hydrological and geological characteristics. While Hillslope 1 was referenced in Line 116 of the original manuscript, the other hillslopes were not explicitly discussed in the corresponding section. To address this, we will update the relevant sections to refer to all three hillslopes, providing a more comprehensive overview. In the revised manuscript, we will include an explanation in Section 2 to describe the selection criteria, locations, and specific research focus of each hillslope.
Comment 31:
Lines 31-33. The authors conclude that their fundings “enhance our understanding of delayed stormflow generation in similar regions”. I think it would be nice to better explain this. Where? Why?
Response 31:
Thank you for your insightful comment regarding the concluding sentence in Abstract. We appreciate your suggestion to provide additional explanation about the applicability of our findings to better explain the broader implications of our study. We will specify the geographical and hydrological contexts where the findings are applicable, as well as the theoretical contributions. The updated text reads:
"These findings advance the understanding of delayed stormflow mechanisms in semi-humid mountainous watersheds, contributing to refining runoff generation theories by providing insights into the threshold-driven processes that govern the timing and volume of delayed stormflow."
Comment 32:
I understand section 3.3 refers to the 14 selected events, is that right?
Response 32:
Thank you for your question. Yes, the analysis in Section 3.3 is indeed based on the 14 selected rainfall-runoff events. These events were carefully chosen to ensure consistency in the data and to focus on scenarios that exhibited clear dynamics in both groundwater level (GWL) and soil water content (SWC). This selection allowed us to examine the distinct GWL response patterns (quick and slow) in greater detail and under comparable conditions.
To clarify this in the manuscript, we will add the following statement at the beginning of Section 3.3:
"The analysis presented in this section is based on 14 selected rainfall-runoff events, which were chosen for their clear and consistent GWL and SWC dynamics, enabling a detailed investigation of groundwater response patterns during storm events."
Comment 33:
Figure 8. It would be nice to have a little map displaying the location of the wells.
Response 33:
Thank you for your valuable suggestion. We will redraw Figure 1 and updated the inset maps showing the spatial distribution of the six wells across the watershed, which will provide a clearer and more detailed view of the locations of the wells. Thank you again for your valuable feedback.
Comment 34:
Figure 9 is nice but difficult to understand with the little information we have about the catchment.
Response 34:
Thank you for your positive feedback on Figure 9 and for highlighting the need for more information about the catchment. We agree that providing additional context about the catchment and the observational setup would help readers better understand the figure.
To address this, we propose the following modifications to the manuscript and Figure 9:
- Expand the caption of Figure 9:
We will expand the caption to provide a more detailed explanation of the figure components, including the phases of SWC changes (orange and green bars) and the significance of SWC thresholds (SWC₀ and SWCG).
- Enhance catchment description in the text:
We will expand on the description of the catchment in Section 2 (Study Site), including more information about the topography, soil properties, and geological structures affecting groundwater level (GWL) and soil water content (SWC). This will help contextualize the differences in GWL and SWC dynamics across hillslopes. The added content including:
“…Based on field investigations and borehole core samples, the underlying granite bedrock exhibits varying degrees of weathering, with highly fractured and permeable layers extending to depths of 10–30 m in certain locations. These layers facilitate vertical and lateral subsurface flow, contributing to the delayed groundwater response observed in the catchment.”
“The surface soil layer is enriched with organic matter due to the extensive forest cover, with humus layers exceeding 10 cm in some areas, enhancing infiltration and reducing the potential for surface runoff.”
- Add a reference to Figure 1 in the text:
To assist readers in connecting the spatial distribution of the wells with the groundwater level (GWL) dynamics depicted in Figure 9, we will add cross-references to Figures 1 within the text discussing Figure 9.
Comment 35:
Figure 10: I understand there are two points per event in that graph. Would be nice to know which points refer to Ts1-ts3 and which to ts2-ts3. I wonder if it is correct to use these two points per event to draw a regression line. The x axis indicates that there is 10 days difference between the reaction in one well and another. I do not understand this and I think the paper do not provide enough evidence to the reader to show what is going on. Why the others wells were not included in the analysis?
Response 35:
Thank you for your constructive feedback regarding Figure 10. Your observations have helped us identify areas where additional clarification and evidence are required. Below, we will address your concerns point by point:
- Clarification of points in Figure 10
We will update Figure 10 to visually distinguish the two points per event by using blue diamonds for ∆t = tS1 - tS3 and red triangles for ∆t = tS2 - tS3. This visual differentiation will improve interpretability and makes it easier to identify the two categories of points.
- Rationale for regression analysis
The regression line in Figure 10 captures the overall relationship between ∆t and peak IG, offering valuable insights into how peak IG governs the synchronization of GWL responses across hillslopes. By including both ∆t = tS1 - tS3 and ∆t = tS2 - tS3 in the same regression, we provide a broader understanding of inter-hillslope dynamics and their dependence on peak IG.
- Explanation of the time difference on the x-axis
We will expand the discussion in Section 3.5 to explain how geological differences among hillslopes influence GWL response times. Specifically, HS3, characterized by thicker regolith and fractured bedrock, exhibits slower GWL responses, while HS1 and HS2 respond more quickly due to higher hydraulic conductivity. These geological differences underline the variability in lag times and justify the calculation of ∆t for inter-hillslope comparisons.
- Inclusion of all wells in the analysis
We will clarify in the revised manuscript that tS1, tS2, and tS3 represent the average lag times of peak GWL calculated from all wells on HS1, HS2, and HS3, respectively. This approach ensures that the analysis incorporates the spatial variability of GWL responses within each hillslope and provides a comprehensive representation of inter-hillslope dynamics.
- Revise Figure caption:
The caption for Figure 10 will be revised for clarity: " Correlation between peak IG and the elapsed times from tS1, tS2 to tS3 (∆t = tS - tS3). tS1, tS2, and tS3 are the average lag times of peak GWL on HS1, HS2, and HS3, respectively."
All these revisions will be included in the revised manuscript, and we appreciate your suggestion for improving the clarity and depth of our manuscript.
Citation: https://doi.org/10.5194/egusphere-2024-2177-AC2
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