the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 30 May 2024
Investigation of Different Roughness Approaches and Vegetation Height Effects on rain-induced overland flow
Abstract. Overland flow is a critical aspect of the hydrological cycle, and understanding its dynamics is crucial for managing water-related issues such as flooding and soil erosion. This paper investigates the impact of various roughness estimation methods on simulating overland flow during intense rain events, with a specific focus on the influence of vegetation. The study assesses various approaches to vary roughness as a function of water sheet thickness and vegetation height, including two different constant Manning's coefficients, a linear approach, an exponential function, a power law function, an empirical formula, and a physics-based approach. The investigation emphasizes the importance of accurate roughness estimation for improving the reliability of hydrological models and enhancing flood prediction capabilities. Experimental data from artificial rainfall experiments on 22 different natural hillslopes in Germany are used to calibrate the OpenLISEM hydrological model, adjusting parameters such as saturated hydraulic conductivity and soil suction at the wetting front. Subsequently, various Manning's coefficient estimation methods are applied, and the model's performance is evaluated numerically.
Preliminary results indicate satisfactory calibration outcomes, with NSE values ranging from 0.75 to 0.95 in most cases for various sites. To validate the models, 100 different experimental rainfall events are used for each roughness method. Validation findings suggest that the physics-based approach, the linear function, and constant Manning roughness, demonstrate the best performance based on NSE values. According to our results, areas with more vegetation coverage demonstrate higher saturated hydraulic conductivity value, indicating that, for two sites with the same soil type, the locations with dense vegetation exhibit higher infiltration parameters. Consequently, it is crucial to evaluate the influence of vegetation on runoff, considering not only its effects on Manning's coefficient but also on saturated hydraulic conductivity.
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RC1: 'Comment on egusphere-2024-1276', Anonymous Referee #1, 22 Oct 2024
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This manuscript compares performance of several overland flow models of previously published experimental data. The manuscript suffers from poor organization, and it is difficult to sift through details to get the broad picture, and, inversely, to find details that are sprinkled throughout. The focus on detailed reporting of statistical fit parameters throughout limits the utility of the manuscript because it comes at the expense of clarity in the reasons for the performances. The introduction does not separate detailed thoughts from main ideas, and it even contains methodological choices mixed in with the background. Two of the three objectives listed in bullet points too broad to be tested. The discussion is written mostly from the perspective of which models perform better practically, not on what modeling concepts best match the physical processes they are intended to mirror. This perspective is especially limiting given that the paper is focused mainly on one set of experimental results—no matter how good those experiments are. The conclusions oddly emphasize the importance of modeling infiltration, rather than on roughness as emphasized in the introduction.
Detailed comments
L28 citation please for constant velocity profile with emergent vegetation
L58 citation please for OpenLISEM. The Jetten (2002) ref is for LISEM. Maybe that’s being picky, but it’s important to be precise about the theory and methods.
References to the theoretical origins of LISEM would be much better. The model predates 2002. Also Jetten 2002 is difficult to obtain.
L100 the first two sentences are unrelated to Methods
L143 assumed by who and for what purposes?
L153 impact on what?
L159-165 are not study site.
Fig 3 is the overland flow mm/min? It would be better if the rain and flow were the same units, but at least the time basis for the flow must be specified.
The naming of the experiments is difficult to access. Why not use more intuitive names instead of number codes?
Percent bias is not defined anywhere. It is also inconsistently named, e.g., as “percentage of bias,” “bias percentage,” and “pBias.”
Saxton and Willey incomplete reference
L225 this paragraph is an example of how poor organization makes it difficult to follow this manuscript. In six sentences, there is a note on anomalously low NSE at one site, a comparison of runoff and rainfall rates at one site, a discussion of how runoff quantity affects model fits, a description of a figure that duplicates figure captions, discussion of differences in Ksat obtained by various methods, and a note that best-fit soil moisture at two sites was different than elsewhere. There is no way to assimilate this information to form a comprehensive picture, and there is no hope of later referring to these disorganized facts.
The results are wordy, overdetailed, and repetitive. For example, most of p 12 is not needed: Table 4 is not needed, L275-280 not needed. L285-288 not needed. Most instances of the word “value” are not needed.
Fig 8 and 9 lack Y axis labels and their meaning is obscure unless the reader remembers how many models there are. Overall, these figures are of low value.
Fig 10 why are some cells green?
L321 if these sites should not be compared to the others, they should not be presented in a figure comparing the sites.
Discussion on the importance of antecedent conditions ought not lead with a citation to a catchment modeling text. Catchment responses are not the subject of this work.
The frequent citation of Feldman et al. (2023) indicates insufficient original content in this manuscipt.
The discussion is just as disorganized as the rest of the manuscript. For example, section 5.3 on vegetation coverage is mainly focused on Ksat and infiltration. I thought this paper was about roughness?
Citation: https://doi.org/10.5194/egusphere-2024-1276-RC1 -
AC1: 'Reply on RC1', Azam Masoodi, 06 Nov 2024
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We appreciate the reviewer’s insightful and constructive feedback and intend to revise the paper accordingly. The misalignment between the introduction and conclusion may have resulted from an evolving focus in our study. Initially, our aim was to evaluate how different roughness estimation methods affect the accuracy of model predictions when compared to physical measurements. However, our results revealed that, in the presence of vegetation, saturated hydraulic conductivity plays a critical role that cannot be ignored. This insight led us to emphasize infiltration parameters in the conclusions, which may have created some confusion for readers.
To address this, we will revwrite the abstract, introduction, and discussion to clarify the role of infiltration in our study and refine the stated objectives to provide a clearer framework for readers.
Additionally, we compared our results with a related study by Feldman et al. (2023), as both studies share the same experimental data set and a similar objective but use different approaches. Feldman et al. extrapolated a nearly constant infiltration rate for the falling limb of the hydrograph, which allowed them to separate the impact of roughness on hydrograph shape from infiltration effects. Our approach, however, considers infiltration across the entire hydrograph. To highlight the differences between these approaches and the importance of considering infiltration effects, we referenced to this paper frequently. However, we did not emphasize the relation to the paper enough in the introduction, which will be changed in a revised version.
Below are our responses to the detailed comments, along with our plan to improve the manuscript’s clarity and organization.
Detailed Comments
Comment L28: The sentence has been modified for better clarity, and a relevant citation has been added at this point in the text.
Comment L58: OpenLISEM is the open-source version of LISEM. We explained about it in L58 and updated the citation in L60 and 63.
Comment L100: these sentences were deleted.
Comment L143: This text “Nevertheless, they do not provide information on the ℎ₀ value. Consequently, this parameter is assumed to be 5 times the plant height for each experimental site” was changed to “As Feldmann et al., (2023) did not provide information on the ℎ₀ value, we assumed ℎ₀ to be five times the plant height to apply the Kadlec’s method in our study.”
Comment L153: “on overland flow” was inserted to the text.
Comment L159-165: We changed the title of this section to “Study site and experimental setup”
Comment on Figure 3: The picture was modified.
Comment on Experiment Naming: A table describing each experiment was added in Section 2.3 for easier access.
Comment on Percentage of Bias: It was modified in the manuscript.
Comment on Saxton and Willey Reference: The reference was completed.
Comment on Figures 8 and 9: These figures are modified.
Comment on Figure 10: An explanation for the green cells is added below the figure.
Comment on L321: We removed these sites from the Figure. 11
Comment on antecedent conditions: We have modified the discussion on antecedent conditions and removed the citations related to catchment modeling.
Citation: https://doi.org/10.5194/egusphere-2024-1276-AC1
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AC1: 'Reply on RC1', Azam Masoodi, 06 Nov 2024
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Model code and software
modified_manning_console Philipp Kraft https://github.com/philippkraft/openlisem/tree/modified_manning_console
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