Geomorphic indicators of continental-scale landscape transience in the Hengduan Mountains, SE Tibet, China

Gelwick, Katrina D.; Willett, Sean D.; Yang, Rong

doi:https://doi.org/10.5194/egusphere-2023-2303

Preprints

https://doi.org/10.5194/egusphere-2023-2303

Preprints

10 Nov 2023

| 10 Nov 2023

Geomorphic indicators of continental-scale landscape transience in the Hengduan Mountains, SE Tibet, China

Katrina D. Gelwick, Sean D. Willett, and Rong Yang

Abstract. Landscapes are sculpted by a complex response of surface processes to external forcings, such as climate and tectonics. Several major river captures have been documented in the Hengduan Mountains, leading to the hypothesis that the region experiences exceptionally high rates of drainage reorganization driven by horizontal shortening and propagating uplift. Here we determine the prevalence, intensity, and spatial patterns of ongoing drainage reorganization in the Hengduan Mountains and evaluate the relative time scales of this transience by comparing drainage divide asymmetry for four geomorphic metrics that operate at different spatial and temporal scales. Specifically, we calculate the migration direction and the divide asymmetry index (DAI) drainage divide asymmetry in catchment-restricted topographic relief (CRR), hillslope gradient (HSG), normalized channel steepness (k_sn), and normalized channel distance (χ). k_sn and χ are both precipitation-corrected to account for the strong precipitation gradient across the region. The different spatial scales of these geomorphic metrics allow us to establish the relative timescales of observed landscape transience in the Hengduan Mountains, where local scale metrics measure short-term change and integral quantities measure long-term disequilibrium. We find a high incidence of strongly asymmetric divides in all metrics across the Hengduan Mountain region. Although the magnitude of asymmetry varies significantly between metrics, possibly due to a combination of metric-specific thresholds and varying proxy relationships with erosion rate, a majority of divides agree on divide migration direction. Agreement in divide migration direction indicates active landscape response when asymmetry is high and a state of quasi-equilibrium when asymmetry is low. Disagreements between the integral quantity, χ, and the other geomorphic metrics can be explained by different timescales of the underlying geomorphic processes, with χ reflecting a long-term response and CRR, HSG, and k_sn capturing short-term perturbations to catchment structure. These perturbations include various transient mechanisms, such as differential tectonic uplift or erodibility, glacial alteration, and river captures. Our work confirms the high incidence of drainage reorganization across the Hengduan Mountains and highlights both transient and stable areas in the landscape with high resolution. We also offer valuable insights on the application of geomorphic metrics that can be generalized and applied to the study of landscape transience and drainage divide asymmetry in other settings.

Received: 09 Oct 2023 – Discussion started: 10 Nov 2023

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Katrina D. Gelwick, Sean D. Willett, and Rong Yang

Status: closed

RC1:
'Comment on egusphere-2023-2303', Anonymous Referee #1, 07 Dec 2023
General comments:

In this contribution, Gelwick et al., presents an analysis of topography mostly associated with drainage divides in the Hengduan Mountains, with an additional focus on comparing the implications and predictions of a variety of divide stability / mobility metrics. Overall, the paper is well organized and clearly written. Drainage divide stability remains a topic of general interest within the geomorphology community, especially so in this particular region of the world, so the paper seems appropriate for ESurf in terms of audience. The majority of my comments on the paper are minor, which I can classify into three broad themes that I summarize below and then flesh out in line-by-line comments.

There are a variety of places where it seems like it would be good to cite additional papers and/or acknowledge prior work more clearly.

In part related to the first point, in a few places in the manuscript the authors seem to imply that the comparison between divide metrics is novel and/or that the general conclusions of comparing different divide metrics, either in the abstract or in specific landscapes is new, when in fact there are a variety of efforts in the prior literature, some that they cite and others that they don’t (e.g., Forte & Whipple, 2018; Sassolas-Serrayet et al., 2019; Ye et al., 2022; Zhou et al., 2022). There is still definitely value in the detailed comparisons presented here, but at the same time, it would be good to acknowledge that many of these same points have been demonstrated by others before.

Finally, there could be some additional discussion of the methods in terms of how the values of the metrics are considered with respect to each other. At present, the methods rely heavily on readers knowing the specific operation of the referenced TopoToolbox functions to sort of follow what is being done, in even in the event that you do, it remains unclear exactly how they’re treating some of the values. I highlight a specific example in the line-by-line comments.

Line-by-line comments:

L44-51: In this section, it seems worthwhile to highlight that the interpretation of this landscape in the context of surface uplift from drainage capture is not without controversy (Whipple, DiBiase, et al., 2017a, 2017b; Willett, 2017).

L58: It might be prudent to add Forte & Whipple, (2018) to this list as the use of some of the metrics you list were more formally defined there as opposed to the cited Whipple et al., (2017).

L180-182: A minor quibble, but while it’s clear that you’re calculating the same thing as Adams et al., (2020), is there a demonstrable reason why you’re not using the same name as in Adams or other subsequent papers (e.g., Leonard et al., 2023; Leonard & Whipple, 2021)? While I would tend to agree that k_snPmight be a more apt name since it incorporates a routed version of mean annual precipitation and thus is not truly discharge (as is effectively implied by calling it k_snQas in Adams, etc.), I also would argue that it’s generally a bad practice to knowingly introduce ambiguity into the literature by arbitrarily renaming a quantity that has been given a particular name in multiple publications.

L201-205: This could be explained a little better. If I follow what you’re doing, you calculate the mean upstream value of a given metric for the entire drainage network and then map values from the streams onto divides, which effectively “follows” the FLOWobj up the stream to divide segments? If that is correct, it seems like there should be a little more discussion of the implications of some of these. For example, in a case where a divide is basically between interfluves, would the upstream mean of the main channels (that are nominally orthogonal to this portion of the divide) be mapped with values from these main channels? If that’s the case, is the across divide contrast relevant? It’s easier to think about a scenario where a divide is between two channel heads with accumulating area above them, but in this case, it’s not necessarily clear whether this method is appropriate for all metrics. Specifically, if you’re treating k_sn / k_snP in this way, that seems problematic as the upslope mean of k_sn above a channel head would be basically the colluvial portion of the profile (where k_snis probably not really a valid metric to calculate). Clarification on these points would help readers understand both what you’re doing, but also how to interpret your results.

L243-255: Throughout this section, you refer to supplemental figures S2 and S3 a lot, making it pretty hard to follow this section without referring to the supplement many times. I wonder if it might be better to move these two figures to the main text since you rely on them heavily.

L289-294: As this is not a new insight in general terms (e.g., it’s a central point of Forte & Whipple, 2018, among other papers), it would be good to add citations to indicate as such.

L296-297: Did you mean to cite Adams here? It’s not clear how that paper is relevant to the point you’re making?

L319-324: This all makes sense, but the extent to which this is or is not a problem within your datasets are hard to assess. I.e., while it’s certainly true that a particular metric on one (or both) side(s) of the divide effectively reaching its threshold would lead to underestimates of what the “true” DAI should be, this is only relevant if the metrics are in the right range, no? While this is a bit challenging to know a priori since there are not single global values of what appropriate thresholds for each metric are and it’s not unreasonable to assume that some (or maybe even many) metrics may be near or at threshold given the tectonic activity of the region, it would be good to have some assessment of whether many (or any) of the raw values of the chosen metric display a threshold like behavior. I.e., if you just plotted all hillslope gradients on a histogram, do you see a distribution that’s reflective of many values being at/near a suite of thresholds?

L324-325: Even without the context of thresholds, this seems prudent as it’s not clear from first principles that a particular DAI based on different metrics would be expected to lead to the same rate of divide migration.

References cited in this review:

Adams, B. A., Whipple, K. X., Forte, A. M., Heimsath, A. M., & Hodges, K. V. (2020). Climate controls on erosion in tectonically active landscapes. Science Advances, 6(42). https://doi.org/10.1126/sciadv.aaz3166
Forte, A. M., & Whipple, K. X. (2018). Criteria and tools for determining drainage divide stability. Earth and Planetary Science Letters, 493, 102–117. https://doi.org/10.1016/j.epsl.2018.04.026
Leonard, J. S., & Whipple, K. X. (2021). Influence of Spatial Rainfall Gradients on River Longitudinal Profiles and the Topographic Expression of Spatially and Temporally Variable Climates in Mountain Landscapes. Journal of Geophysical Research: Earth Surface, 126(12). https://doi.org/10.1029/2021JF006183
Leonard, J. S., Whipple, K. X., & Heimsath, A. M. (2023). Isolating climatic, tectonic, and lithologic controls on mountain landscape evolution. Science Advances, 9(3), eadd8915. https://doi.org/10.1126/sciadv.add8915
Sassolas-Serrayet, T., Cattin, R., Ferry, M., Godard, V., & Simoes, M. (2019). Estimating the disequilibrium in denudation rates due to divide migration at the scale of river basins. Earth Surface Dynamics, 7(4), 1041–1057. https://doi.org/10.5194/esurf-7-1041-2019
Whipple, K. X., DiBiase, R. A., Ouimet, W. B., & Forte, A. M. (2017a). Preservation or piracy: Diagnosing low-relief, high-elevation surface formation mechanisms. Geology, 45, 91–94. https://doi.org/10.1130/G38490.1
Whipple, K. X., DiBiase, R. A., Ouimet, W. B., & Forte, A. M. (2017b). Preservation or piracy: Diagnosing low-relief, high-elevation surface formation mechanisms REPLY. Geology, 45(8). https://doi.org/10.1130/G39252Y.1
Whipple, K. X., Forte, A. M., DiBiase, R. A., Gasparini, N. M., & Ouimet, W. B. (2017). Timescales of landscape response to divide migration and drainage capture: Implications for the role of divide mobility in landscape evolution. Journal of Geophysical Research: Earth Surface. https://doi.org/10.1002/2016JF003973
Willett, S. (2017). Preservation or piracy: Diagnosing low-relief, high-elevation surface formation mechanism COMMENT. Geology, 45(8). https://doi.org/10.1130/G3829C.1
Ye, Y., Tan, X., & Zhou, C. (2022). Initial topography matters in drainage divide migration analysis: Insights from numerical simulations and natural examples. Geomorphology, 409, 108266. https://doi.org/10.1016/j.geomorph.2022.108266
Zhou, C., Tan, X., Liu, Y., Lu, R., Murphy, M. A., He, H., et al. (2022). Ongoing westward migration of drainage divides in eastern Tibet, quantified from topographic analysis. Geomorphology, 402, 108123. https://doi.org/10.1016/j.geomorph.2022.108123
Citation: https://doi.org/10.5194/egusphere-2023-2303-RC1
- AC1: 'Reply on RC1', Katrina Gelwick, 23 Jan 2024
  
  We thank Anonymous Referee #1 for this constructive and helpful review that has improved the manuscript. Please find our comment-by-comment response in the attached PDF.
  
  Citation: https://doi.org/10.5194/egusphere-2023-2303-AC1
RC2:
'Comment on egusphere-2023-2303', Anonymous Referee #2, 14 Dec 2023

Review of “Geomorphic indicators of continental-scale landscape transience in the Hengduan Mountains, SE Tibet, China” by Gelwick et al.
General comments
This work investigated drainage divide asymmetry of the Hengduan Mountains (HDM) using four geomorphic metrics (CRR, HSG, ksnP, and χP) to understand the spatial and temporal patterns of geometric transience of river network in this region. They find clear evidence of widespread transience through a high incidence of strongly asymmetrical divides throughout the HDM with the four geomorphic metrics. The study of landscape transient effect in this complex area is challenging, and the work provides such test using four metrics, and compare the difference between these metrics. From these new aspects, the manuscript is suitable for publishing in ESurf. However, the manuscript may have some problems on the geomorphic metrics that need to be addressed and which may require substantial revision.
(1) ksn and χ are both precipitation-corrected to account the strong precipitation gradient in this region in equations (4) and (6), but the authors seem use the ‘local’ mean annual precipitation P, in fact it should be the ‘upstream’ mean annual precipitation of a reference point, i.e., rainfall rate averaged over A, according to Adams et al. (2020). Local and upstream average are quite different.
(2) For calculating the χ and χP, the authors chose a base-level of 500 m for the study area to approximate the elevation at the western edge of the Sichuan Basin. This is fine for a base-level of most streams of the Yangtze River in the HDM. However, the work mainly studies the transience of the HDM in the Three Rivers region (not only the Yangtze River), which have three different outlets. Whether the results and conclusions are sensitive if the base-level elevations are set to 1000 m or 1500m, which are approximately at the plateau margin.
Specific comments (by line)

Lines 11-12: The authors claim that they evaluate the relative time scales of this transience by comparing drainage divide asymmetry, but I did not see any time scales of transience in this work.
Lines 88-90: There are many one-sentence paragraphs in the manuscript, it is quite strange to have one-sentence paragraphs, try to minimize them.
Lines 178-179: The authors refer to Fig. S2 “A best-fit θref of 0.45 was determined for the HDM through Bayesian optimization with the mnoptim function in Topotoolbox”, but Fig. S2 is not on the river concavity, missing a figure?
Lines 183-184 and Fig. S1: Maybe put ksn and ksnP, χ and χP together for easy of comparing? One-sentence of paragraph is not necessary here.
Lines 238-240: It seems that the threshold for “high” (95th percentile) and “low” (5th percentile) divide asymmetry in each metric is chosen arbitrary?
Lines 243-249 and Fig. S2: The authors explain the difference of highly asymmetric drainage divides between χ and χP, but I did not understand by looking at the Fig. S2. It is better to show an overlap figure marking the difference between metrics χ and χP, and a figure marking the difference between metrics ksn and ksnP.
Fig. 3. It is very difficult to understand this figure. It took much of my time to understand it. I suggest simplifying this figure. For example, changing the y-axis in right-hand side to the grey color. Move ‘%’ in y-axis of the left-hand side to the end of Migration direction agreement. Check the unit of KsnP, the unit of Ksn is m^0.9, but KsnP has considered the precipitation with unit of m/yr.
All equations require a common or a point in the end, they are currently missing throughout the manuscript.
I hope that these comments are helpful for the revision.

Citation: https://doi.org/10.5194/egusphere-2023-2303-RC2
- AC2: 'Reply on RC2', Katrina Gelwick, 23 Jan 2024
  
  We would like to thank Anonymous Referee #2 for their thorough review and constructive comments. We agree with the reviewer on most points and have adjusted the text and figures accordingly. Their comments have also identified places where the manuscript benefited from further clarification. Please find our comment-by-comment response in the attached PDF.
  
  Citation: https://doi.org/10.5194/egusphere-2023-2303-AC2

Status: closed

RC1:
'Comment on egusphere-2023-2303', Anonymous Referee #1, 07 Dec 2023
General comments:

In this contribution, Gelwick et al., presents an analysis of topography mostly associated with drainage divides in the Hengduan Mountains, with an additional focus on comparing the implications and predictions of a variety of divide stability / mobility metrics. Overall, the paper is well organized and clearly written. Drainage divide stability remains a topic of general interest within the geomorphology community, especially so in this particular region of the world, so the paper seems appropriate for ESurf in terms of audience. The majority of my comments on the paper are minor, which I can classify into three broad themes that I summarize below and then flesh out in line-by-line comments.

There are a variety of places where it seems like it would be good to cite additional papers and/or acknowledge prior work more clearly.

In part related to the first point, in a few places in the manuscript the authors seem to imply that the comparison between divide metrics is novel and/or that the general conclusions of comparing different divide metrics, either in the abstract or in specific landscapes is new, when in fact there are a variety of efforts in the prior literature, some that they cite and others that they don’t (e.g., Forte & Whipple, 2018; Sassolas-Serrayet et al., 2019; Ye et al., 2022; Zhou et al., 2022). There is still definitely value in the detailed comparisons presented here, but at the same time, it would be good to acknowledge that many of these same points have been demonstrated by others before.

Finally, there could be some additional discussion of the methods in terms of how the values of the metrics are considered with respect to each other. At present, the methods rely heavily on readers knowing the specific operation of the referenced TopoToolbox functions to sort of follow what is being done, in even in the event that you do, it remains unclear exactly how they’re treating some of the values. I highlight a specific example in the line-by-line comments.

Line-by-line comments:

L44-51: In this section, it seems worthwhile to highlight that the interpretation of this landscape in the context of surface uplift from drainage capture is not without controversy (Whipple, DiBiase, et al., 2017a, 2017b; Willett, 2017).

L58: It might be prudent to add Forte & Whipple, (2018) to this list as the use of some of the metrics you list were more formally defined there as opposed to the cited Whipple et al., (2017).

L180-182: A minor quibble, but while it’s clear that you’re calculating the same thing as Adams et al., (2020), is there a demonstrable reason why you’re not using the same name as in Adams or other subsequent papers (e.g., Leonard et al., 2023; Leonard & Whipple, 2021)? While I would tend to agree that k_snPmight be a more apt name since it incorporates a routed version of mean annual precipitation and thus is not truly discharge (as is effectively implied by calling it k_snQas in Adams, etc.), I also would argue that it’s generally a bad practice to knowingly introduce ambiguity into the literature by arbitrarily renaming a quantity that has been given a particular name in multiple publications.

L201-205: This could be explained a little better. If I follow what you’re doing, you calculate the mean upstream value of a given metric for the entire drainage network and then map values from the streams onto divides, which effectively “follows” the FLOWobj up the stream to divide segments? If that is correct, it seems like there should be a little more discussion of the implications of some of these. For example, in a case where a divide is basically between interfluves, would the upstream mean of the main channels (that are nominally orthogonal to this portion of the divide) be mapped with values from these main channels? If that’s the case, is the across divide contrast relevant? It’s easier to think about a scenario where a divide is between two channel heads with accumulating area above them, but in this case, it’s not necessarily clear whether this method is appropriate for all metrics. Specifically, if you’re treating k_sn / k_snP in this way, that seems problematic as the upslope mean of k_sn above a channel head would be basically the colluvial portion of the profile (where k_snis probably not really a valid metric to calculate). Clarification on these points would help readers understand both what you’re doing, but also how to interpret your results.

L243-255: Throughout this section, you refer to supplemental figures S2 and S3 a lot, making it pretty hard to follow this section without referring to the supplement many times. I wonder if it might be better to move these two figures to the main text since you rely on them heavily.

L289-294: As this is not a new insight in general terms (e.g., it’s a central point of Forte & Whipple, 2018, among other papers), it would be good to add citations to indicate as such.

L296-297: Did you mean to cite Adams here? It’s not clear how that paper is relevant to the point you’re making?

L319-324: This all makes sense, but the extent to which this is or is not a problem within your datasets are hard to assess. I.e., while it’s certainly true that a particular metric on one (or both) side(s) of the divide effectively reaching its threshold would lead to underestimates of what the “true” DAI should be, this is only relevant if the metrics are in the right range, no? While this is a bit challenging to know a priori since there are not single global values of what appropriate thresholds for each metric are and it’s not unreasonable to assume that some (or maybe even many) metrics may be near or at threshold given the tectonic activity of the region, it would be good to have some assessment of whether many (or any) of the raw values of the chosen metric display a threshold like behavior. I.e., if you just plotted all hillslope gradients on a histogram, do you see a distribution that’s reflective of many values being at/near a suite of thresholds?

L324-325: Even without the context of thresholds, this seems prudent as it’s not clear from first principles that a particular DAI based on different metrics would be expected to lead to the same rate of divide migration.

References cited in this review:

Adams, B. A., Whipple, K. X., Forte, A. M., Heimsath, A. M., & Hodges, K. V. (2020). Climate controls on erosion in tectonically active landscapes. Science Advances, 6(42). https://doi.org/10.1126/sciadv.aaz3166
Forte, A. M., & Whipple, K. X. (2018). Criteria and tools for determining drainage divide stability. Earth and Planetary Science Letters, 493, 102–117. https://doi.org/10.1016/j.epsl.2018.04.026
Leonard, J. S., & Whipple, K. X. (2021). Influence of Spatial Rainfall Gradients on River Longitudinal Profiles and the Topographic Expression of Spatially and Temporally Variable Climates in Mountain Landscapes. Journal of Geophysical Research: Earth Surface, 126(12). https://doi.org/10.1029/2021JF006183
Leonard, J. S., Whipple, K. X., & Heimsath, A. M. (2023). Isolating climatic, tectonic, and lithologic controls on mountain landscape evolution. Science Advances, 9(3), eadd8915. https://doi.org/10.1126/sciadv.add8915
Sassolas-Serrayet, T., Cattin, R., Ferry, M., Godard, V., & Simoes, M. (2019). Estimating the disequilibrium in denudation rates due to divide migration at the scale of river basins. Earth Surface Dynamics, 7(4), 1041–1057. https://doi.org/10.5194/esurf-7-1041-2019
Whipple, K. X., DiBiase, R. A., Ouimet, W. B., & Forte, A. M. (2017a). Preservation or piracy: Diagnosing low-relief, high-elevation surface formation mechanisms. Geology, 45, 91–94. https://doi.org/10.1130/G38490.1
Whipple, K. X., DiBiase, R. A., Ouimet, W. B., & Forte, A. M. (2017b). Preservation or piracy: Diagnosing low-relief, high-elevation surface formation mechanisms REPLY. Geology, 45(8). https://doi.org/10.1130/G39252Y.1
Whipple, K. X., Forte, A. M., DiBiase, R. A., Gasparini, N. M., & Ouimet, W. B. (2017). Timescales of landscape response to divide migration and drainage capture: Implications for the role of divide mobility in landscape evolution. Journal of Geophysical Research: Earth Surface. https://doi.org/10.1002/2016JF003973
Willett, S. (2017). Preservation or piracy: Diagnosing low-relief, high-elevation surface formation mechanism COMMENT. Geology, 45(8). https://doi.org/10.1130/G3829C.1
Ye, Y., Tan, X., & Zhou, C. (2022). Initial topography matters in drainage divide migration analysis: Insights from numerical simulations and natural examples. Geomorphology, 409, 108266. https://doi.org/10.1016/j.geomorph.2022.108266
Zhou, C., Tan, X., Liu, Y., Lu, R., Murphy, M. A., He, H., et al. (2022). Ongoing westward migration of drainage divides in eastern Tibet, quantified from topographic analysis. Geomorphology, 402, 108123. https://doi.org/10.1016/j.geomorph.2022.108123
Citation: https://doi.org/10.5194/egusphere-2023-2303-RC1
- AC1: 'Reply on RC1', Katrina Gelwick, 23 Jan 2024
  
  We thank Anonymous Referee #1 for this constructive and helpful review that has improved the manuscript. Please find our comment-by-comment response in the attached PDF.
  
  Citation: https://doi.org/10.5194/egusphere-2023-2303-AC1
RC2:
'Comment on egusphere-2023-2303', Anonymous Referee #2, 14 Dec 2023

Review of “Geomorphic indicators of continental-scale landscape transience in the Hengduan Mountains, SE Tibet, China” by Gelwick et al.
General comments
This work investigated drainage divide asymmetry of the Hengduan Mountains (HDM) using four geomorphic metrics (CRR, HSG, ksnP, and χP) to understand the spatial and temporal patterns of geometric transience of river network in this region. They find clear evidence of widespread transience through a high incidence of strongly asymmetrical divides throughout the HDM with the four geomorphic metrics. The study of landscape transient effect in this complex area is challenging, and the work provides such test using four metrics, and compare the difference between these metrics. From these new aspects, the manuscript is suitable for publishing in ESurf. However, the manuscript may have some problems on the geomorphic metrics that need to be addressed and which may require substantial revision.
(1) ksn and χ are both precipitation-corrected to account the strong precipitation gradient in this region in equations (4) and (6), but the authors seem use the ‘local’ mean annual precipitation P, in fact it should be the ‘upstream’ mean annual precipitation of a reference point, i.e., rainfall rate averaged over A, according to Adams et al. (2020). Local and upstream average are quite different.
(2) For calculating the χ and χP, the authors chose a base-level of 500 m for the study area to approximate the elevation at the western edge of the Sichuan Basin. This is fine for a base-level of most streams of the Yangtze River in the HDM. However, the work mainly studies the transience of the HDM in the Three Rivers region (not only the Yangtze River), which have three different outlets. Whether the results and conclusions are sensitive if the base-level elevations are set to 1000 m or 1500m, which are approximately at the plateau margin.
Specific comments (by line)

Lines 11-12: The authors claim that they evaluate the relative time scales of this transience by comparing drainage divide asymmetry, but I did not see any time scales of transience in this work.
Lines 88-90: There are many one-sentence paragraphs in the manuscript, it is quite strange to have one-sentence paragraphs, try to minimize them.
Lines 178-179: The authors refer to Fig. S2 “A best-fit θref of 0.45 was determined for the HDM through Bayesian optimization with the mnoptim function in Topotoolbox”, but Fig. S2 is not on the river concavity, missing a figure?
Lines 183-184 and Fig. S1: Maybe put ksn and ksnP, χ and χP together for easy of comparing? One-sentence of paragraph is not necessary here.
Lines 238-240: It seems that the threshold for “high” (95th percentile) and “low” (5th percentile) divide asymmetry in each metric is chosen arbitrary?
Lines 243-249 and Fig. S2: The authors explain the difference of highly asymmetric drainage divides between χ and χP, but I did not understand by looking at the Fig. S2. It is better to show an overlap figure marking the difference between metrics χ and χP, and a figure marking the difference between metrics ksn and ksnP.
Fig. 3. It is very difficult to understand this figure. It took much of my time to understand it. I suggest simplifying this figure. For example, changing the y-axis in right-hand side to the grey color. Move ‘%’ in y-axis of the left-hand side to the end of Migration direction agreement. Check the unit of KsnP, the unit of Ksn is m^0.9, but KsnP has considered the precipitation with unit of m/yr.
All equations require a common or a point in the end, they are currently missing throughout the manuscript.
I hope that these comments are helpful for the revision.

Citation: https://doi.org/10.5194/egusphere-2023-2303-RC2
- AC2: 'Reply on RC2', Katrina Gelwick, 23 Jan 2024
  
  We would like to thank Anonymous Referee #2 for their thorough review and constructive comments. We agree with the reviewer on most points and have adjusted the text and figures accordingly. Their comments have also identified places where the manuscript benefited from further clarification. Please find our comment-by-comment response in the attached PDF.
  
  Citation: https://doi.org/10.5194/egusphere-2023-2303-AC2

Katrina D. Gelwick, Sean D. Willett, and Rong Yang

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https://doi.org/10.5194/egusphere-2023-2303-supplement

Katrina D. Gelwick, Sean D. Willett, and Rong Yang

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Short summary

We evaluated the intensity and spatial extent of landscape change in the Hengduan Mountains by identifying areas where river network reorganization is occurring or expected in the future. We combine four metrics that measure topographic imbalances at different spatial and temporal scales. Our study provides a deeper understanding of the dynamic nature of the Hengduan Mountains' landscape and associated drivers, such as tectonic uplift, and insights for applying similar methods elsewhere.


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