the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 27 Oct 2023
More than one landslide per road kilometer – surveying and modeling mass movements along the Rishikesh-Joshimath (NH-7) highway, Uttarakhand, India
Abstract. The rapidly expanding Himalayan road network connects rural mountainous regions. However, the fragility of the landscape and poor road construction practices lead to frequent mass movements along-side roads. In this study, we investigate fully or partially road-blocking landslides along the National Highway (NH-7) in Uttarakhand, India, between Rishikesh and Joshimath. Based on an inventory of >300 landslides along the ~250 km long corridor following exceptionally high rainfall during September and October, 2022, we identify the main controls on the spatial occurrence of mass-movement events. Our analysis and modeling approach conceptualizes landslides as a network-attached spatial point pattern. We evaluate different gridded rainfall products and infer the controls on landslide occurrence using Bayesian analysis of an inhomogeneous Poisson process model. Our results reveal that slope, rainfall amounts, lithology and road widening are the main controls on landslide occurrence. The individual effects of aggregated lithozones are consistent with previous assessments of landslide susceptibilities of rock types in the Himalayas. Our model spatially predicts landslide occurrences and can be adapted for other rainfall scenarios, and thus has potential applications for efficiently allocating efforts for road maintenance. To this end, our results highlight the vulnerability of the Himalayan road network to landslides. Climate change and increasing exposure along this pilgrimage route will likely exacerbate landslide risk along the NH-7 in the future.
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RC1: 'Comment on egusphere-2023-1975', Anonymous Referee #1, 23 Jan 2024
This paper examines landslide occurrences along a busy highway in India. The authors generate a landslide inventory and analyze corresponding landslide density with respect to some external factors including precipitation, slope and lithology. Overall, it is a publishable work but there are so many points which are not clear to me at all. I have listed all my comments below line-by-line. My main problem with the paper is that the authors do not clearly introduce their methodology and they do not explain reasoning behind choices they made. Therefore, I had a hard time understanding why/how they did some analyses. Following moderate to major revisions, I believe the paper could be publishable.
Lines 29-34. Please cite the relevant literature.
Lines 35-37. Please cite the relevant literature.
Line 37. Considering the flow of your text, the last line of this paragraph is a bit off.
Line 51. Please cite those “few” studies, cite at least some of them.
Lines 61-62. “Limiting the inventory to road blocking landslides was required to cope with the overwhelming number of landslides and to ensure that we account for the landslides that detached most recently.” Could you please elaborate this further? How do you define those “recently occurred” landslides (e.g., “the ones that blocked roads in the last five years”)? And why do you want to put such a restriction to your inventory?
Line 64. “previous studies” Please cite at least some of them.
Line 65. “in two spatial dimensions” No need to indicate this, please remove.
Line 65. “conceptualizes landslides as a network-attached spatial point pattern” Could you please elaborate this further, what do you mean by this? It seems like this is an important element in your methodology and thus, it deserves a bit more attention. What are the main findings of Baddeley and others and how do you think they contribute to the existing literature?
Line 66. “simplified approach” If you provide more explanation we can also have an idea if this is a simplified approach or not.
Lines 71-72. “We present our results and discuss uncertainties and potential shortcomings of our approach. We conclude with recommendations for refinement of the approach and further research avenues” No need for these lines, you need to have a discussion, conclusions and interpretations anyway.
Line 72. “Study site” You can convert this heading to something like “study area and data” because in the method section you mention your data sources although, for instance, in figure 1 you already present your geology map. Thus, you can move those sections here.
Line 75. “1000–1200”mm
Line 115. Method section: Please first provide a summary of your methodology. There are several elements there. If you systematically present your methodology as step1, step2 and so forth, your readers could follow you more easily. For instance, you start with field work and jump into how you mapped landslides. However, it would be better if you list your steps and then explain what you have done (and what datasets you have used) in each of those steps. This is to say that, please first give us a structure and then we can better understand what you did and why you did. In this regard, you can first describe different landslide categories (Figure 1) and indicate those corresponding periods. We need to know the set of criteria you used to label those landslides.
Lines 115-130. It seems like you mapped landslides as points but polygons, right? Please indicate this. Could you also mention where you put those points, to the crown of each landslide? Could you please make a figure showing a close-up view showing examples for each landslide category you mentioned? Please show those examples by providing multi-temporal images, so we can see corresponding conditions in different periods. You are saying you collected some GPS locations during your field work. Then I think you should also show us how you assigned those coordinates to corresponding hillslopes.
What is the importance of labelling landslides as (1) new landslide, (2) road-blocking landslide visible before the Sep–Oct 2022 rainfall anomaly, and (3) reactivated landslide. In your model, there is no difference between them, right? Here my main concern is that if you used the accumulated precipitation for the corresponding period. For instance, you have some landslides that occurred before Sep-Oct 2022 and you do not know when they really occurred. And yet, you used accumulated precipitation between Jan-Oct, 2022. Also, you have some new landslides, which have obviously occurred in a different time window compared to the former category but you still use the same period to calculate the cumulative precipitation. The same is also valid for the reactivated landslides. I think you should clearly indicate time spans where you think landslides either occurred or reactivated and then you should calculate the cumulative precipitation for the given temporal windows for different landslides separately.
Btw, I think I mentioned this above already, but it is worth mentioning again that you should better describe your landslide categories and their corresponding time windows. You can simply add a table so we can clearly see what you refer to in each category.
Line 137. Your readers do not have to know what PPS is, please give the long version of it.
Line 137. How did you calculate your landslide density btw? This is your target variable and it needs further explanation? First of all, why did you target landslide density and why not landslide occurrences? In this case, you have a density value depending on your moving kernel. It could be small but I assume you will have a value for a large portion of the study area. This means that even if there is no landslide you will have a value. Am I correct? I am asking these questions because I could not find answers in the manuscript. Could you show us the distribution of density values via a histogram. What is the spatial resolution that you create for your landslide density map? In the result section, you should show us that landslide density map. I guess you calculated landslide density around the road with 210m-wide buffer zone (?) Is this the boundary of your study area anyway?
Line 145. Could you please explain why you chose a log-linear model
Line 165. You do not need to hypothesize this, so you better cite the relevant literature.
Line 166. “accumulated rainfall” Be careful that some of those satellite products do not provide rainfall data but precipitation. And these are different things.
Lines 180-184. Please show this layer in one of your figures.
Line 197. Please cite the relevant literature and explain how it works.
Line 203. I need further explanation for this section. If you use Poisson regression, then I do not know how you convert it into AUC (You have a continuous array but AUC mainly works for binary conditions). I remember I saw it also before in the literature but you do not either cite the literature nor provide a detailed explanation. Therefore, it is not clear for the moment.
Also, I would expect to see a correlation between predicted landslide density and calculated value. There you can assess your prediction performance via some other statistical measures.
Line 227. “AIC” Akaike Information Criterion. Please first explain this in your method section and cite the literature as this is not your own methodology.
Lines 231-234. This needs to be numerically shown, otherwise you can mention it as a source of uncertainty in your discussion section.
Lines 238-241. This is not presented in any figure nor via a table. Where are the outputs of the Bayesian feature rank algorithm? I would like to see how you come up with this conclusion.
Lines 260-266. This needs to be moved to the discussion section.
Line 287. “this means that spatial variables characterizing the source area (e.g., hillslope gradient) are projected onto the road” What does this mean?
Lines 288-290. I do not think this is relevant, so please remove this. Even if you worked with thousands of landslides that would not be computationally challenging I would say, no?
Line 298. “studies come to different conclusions” But in the following lines you do not mention those different conclusions.
Lines 324-343. “However, we cannot exclude that small-scale topographic changes due to construction or land use changes” You do not know, you are just speculating because you were not able to capture that signal in your model. Therefore, please rewrite this line and make it smoother instead of saying “we cannot exclude”.
Line 357. Please remove footnotes and give citations to online sources.
Figure 1. “The highest density of landslides occurs between Rishikesh and Srinagar within lithozone 2 and between Pipalkoti and Joshimath in lithozone 1.” Please keep this line for your main text and remove it from here.
“For description of the lithozones see Table 2.”In lines 190-191, you mention five lithologic units: (1), phyllite and shale (2), quartzite (3), quartzite and igneous rocks (4) and crystalline high grade metamorphic rocks (5). Please indicate the same units in Figure 1.
“Note that lithozones 0 and 6 are not crossed by the road and are therefore omitted from the description.” Refer to them with their names, please do not use ids.
“We subdivided the landslides into new ones, reactivated ones and those that were blocking the road before September 2022.” Figure captions are just to describe what you present in that figure, it is not to present what you have done. Please say it in the main text not here.
“Stars indicate locations of the 1999 Mw 6.6 Chamoli earthquake (Kayal et al., 2003; USGS, 2022) and the 2021 Chamoli rock and ice avalanche” Which stars are showing which events?
Figure 2. This figure is not enough to present how you mapped landslides. I made some comments above.
Figure 3. Rainfall or precipitation?
Figure 4. “Lithozone 1 is missing since the parameter is encapsulated in the intercept.” I did not understand what you meant here. Please elaborate this in the main text.
Figure 5. First present your predictive variables and then target variables and then finally show you prediction. What are those blue ticks in panel b? How is it possible that accumulated precipitation shows variation in very small distances? The minimum spatial resolution should be 5 km but somehow I see that it changes even within 1 km. Btw, I do not remember if you mention any downscaling but please clarify that point as well if you did not do that.
Table 1. How did you aggregate these units? I see quite similar lithologic units in different categories.
Citation: https://doi.org/10.5194/egusphere-2023-1975-RC1 -
RC2: 'Comment on egusphere-2023-1975', Anonymous Referee #2, 26 Apr 2024
The research by Mey and co-authors proposes a nice analysis on the occurrence and modelling of landslides along a highway in India. Such research focus is clearly needed in the context of the Anthropocene and the growing concern of the influence of human activities on Earth surface processes. This research is therefore timely and well within the scope of NHESS.
Having had a look at the extensive review already carried out by a first referee; I can only agree with him/her that the manuscript must be improved quite substantially in several aspects. In addition to the issues evidenced by the first reviewer, especially with respect to the methodological aspects, I would like to stress extra points that I hope would help in improving this work.
- The introduction is somehow a bit strange as it starts with a focus on the study area, without really providing the broader picture of human-induced problem on landslides, and especially that of road. Besides a need of a broader literature (as stressed by the other referee), on would benefit from a better organization of the introduction structure I think.
- Although the case study on that highway in India is a nice one, we miss somehow the reason why this case study could be of special interest for a broader audience. In other words, why, for example, would someone working in the Andes be interested in such a study. Here some work could be needed to improve the introduction and discussion.
- As the referee says, knowing about the age of the landslides is quite important. However, the age of the road sections is also something that is important. Recent road sections could be much more damaging/impactful on hillslope instability due to, for example, de-buttressing effect that would be more intense in the recent years that follow a new road cut that along cuts of older roads. However, older roads mean also older outcrops, and therefore potentially increased weathering conditions. Maintenance activities and infrastructures to stabilize/drain the road environments can also vary along the road. Overall, I think that information (discussion) on these issues is needed.
- 30 m DEM is used to calculate surface (slope?) gradient. At such a resolution we clearly miss the subtle topographic characteristics that we find along roads. In addition, road cuts would definitely be missed. This issue needs to be clarified in the analyses and/or discussion.
Citation: https://doi.org/10.5194/egusphere-2023-1975-RC2
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