Topographic controls on landslide mobility: Modeling hurricane-induced landslide runout and debris-flow inundation in Puerto Rico
Abstract. In 2017, Hurricane Maria triggered more than 70,000 landslides in Puerto Rico. After initiation, these predominantly shallow landslides mobilized to varying degrees – some landslides only traveled partway downslope, whereas others reached drainages and mobilized into long-traveled debris flows that could severely impact roads and infrastructure. Thus, forecasting potential landslide runout and inundation zones is critical for estimating landslide and debris flow hazards. Here we conduct an in-depth topographic analysis of landslide-affected areas from nine study areas and apply a linked modeling technique to estimate locations susceptible to varying degrees of landslide runout in Lares, Utuado and Naranjito municipalities.
We find that longer runout length is observed on high-relief escarpments, although highly mobile long-runout debris flows also occurred in lower-relief dissected uplands. These topographic differences indicate that landslides initiating under similar conditions and possessing equal potential to mobilize as debris flows may not travel the same distances or affect the same areal extent. Our modeling approach allows the local topography to automatically control the implementation of two runout methods: 1) H/L runout zones are assigned directly downslope of landslide source zones, and 2) debris-flow inundation zones are estimated in the presence of a channel network. Debris-flow volumes are calculated as a function of area-integrated growth factors, estimated as a function of the upstream areas susceptible to shallow landslides. Applying our empirical modeling scheme over an area of 560 km2 , our results highlight the efficacy of our methods for assessment of the potential for landslide runout and debris-flow inundation over diverse terrains with varied susceptibility.
- Preprint
(3976 KB) - Metadata XML
- BibTeX
- EndNote
Status: final response (author comments only)
-
RC1: 'Reviewer comment on nhess-2024-141', Martin Mergili, 28 Oct 2024
The authors analyze landslide mobility related to the 2017 hurricane Maria for three municipalities in Puerto Rico. Based on published landslide inventories and a published slope stability and landslide susceptibility analysis, terrain and geological information, they analyze landslide runout based on empirical models, distinguishing between rather short-runout landslides on slopes (H/L model) and longer runout debris flows in channels. A growth function is applied to account for erosion and landslide input to debris flows, based on topographic and empirical parameters. The results of the debris flow runout model are evaluated against mapped runout zones using an ROC analysis.
The topic investigated is highly relevant from both scientific and practical perspectives. It is certainly suitable for NHESS. The manuscript is very well written, structured, and illustrated. I would certainly like to see this work published in NHESS. I just have two specific comments and suggestions for improvement (see below), so that I recommend some minor revisions. All in all, I congratulate the authors for their excellent work.
Specific comments:
- The work flow of the study is, in principle, clearly presented and nicely illustrated through Fig. 5. There is just one point which is not clear to me: are the datasets used to develop the models and those used to evaluate their predictive success completely independent, or do they overlap? For H/L, it is written in L339 that, besides global datasets, also datasets from Hurricane Maria are used. Are those the same as used for evaluation (L373)? Are there similar issues for the debris flows? If yes, I suggest to address and justify such overlap in one or two sentences.
- The ROC analysis is, again, very well illustrated (Fig. 15) and explained. I am rather familiar with another type of ROC plot and was looking for values of the area under the curve (AUROC), which is very commonly used to evaluate the success of landslide simulations, but I found none. Would it be possible to use AUROC values, or is this just not useful for the type of ROC analysis performed here?
Citation: https://doi.org/10.5194/nhess-2024-141-RC1 -
AC1: 'Reply on RC1', Dianne Brien, 08 Nov 2024
Thank you for the thoughtful comments and suggestions. Here is a reply:
Input datasets for selection of model parameters
For debris-flow inundation modeling, Maria's most mobile landslides (MMM) provided statistics to constrain the range of values for stream order, planform curvature, and Psrc (Table 7). Scenarios defining the location of debris flow growth were built using the extracted statistics in combination with stream slopes measured in the field. Debris-flow growth factors and maximum debris-flow volumes were not available for all MMM. The growth factors and volumes were obtained from Coe et al., 2021. The MMM dataset was used to test the predictive success of the debris flow inundation modeling
For the landslide runout modeling, we explored a variety of published references with H/L values: 1) Hurricane Maria landslides (Bessette-Kirton, 2020), 2) worldwide datasets (Corominas, 1996), and 3) data from flume experiments (Iverson, 1997). Although one might expect that the ideal dataset is Hurricane Maria landslides, we found that median values presented in Bessette-Kirton, 2020 (27 to 34 degrees) would have resulted in an underestimation of runout and a gap between non-channelized runout zones and the channel. Maximum values from Hurricane Maria were from channelized flows – these values would be extremely low (14 degrees). It was apparent that H/L values extracted from regional datasets, such as the Hurricane Maria inventories, are influenced by the local slope and may not be a good metric for landslide mobility when used in this context. H/L is valuable for comparison of mobility when the local slope and hillslope lengths are equivalent. With much of the topography in Puerto Rico consisting of mountainous areas with greater than 40 degree slopes, landslides occurring on these steep slopes that do not make it to the bottom of the hill are common in the inventories and result in high values of α.The inventories included only a small number of landslides in non-channelized topography, hence we resorted to an approach that assesses how much the predicted area of runout is affected by changes in α. We ultimately conclude that 1) H/L values extracted from landslide inventories are strongly influenced by the local slope, and 2) for much of the terrane in Puerto Rico, there is very little difference in the area affected regardless of selected H/L value (Fig. 13). Using the landslide source areas published in the landslide inventories, figure 13 illustrates the minimal change in area affected (added yellow area) with a decrease of α from 25 to 20 degrees.
We attempt to explain the biases in H/L values extracted from regional landslide inventories from widespread landslide-inducing events in the results (6.1) and discussion (7.3.1). Ultimately, we did not quantitively assess predictive success given that in areas with predominantly steep slopes the statistics would have looked good, but this is really a bias in the distribution of topographic slopes rather than an indication of predictive success.
We will work to provide additional clarification in the revisions.
ROC analysis
AUROC values are typically used for comparison of different methods. In this case, one method is applied with different parameters rather than comparing different methods. The consideration of TPR allows direct comparison with the metric used for the source area modeling (Baum et al., 2024). For the intended purpose it is not as useful to extract AUROC values, since we need to identify a point in ROC space where TPR is less than 1.0 (TPR=1 is unobtainable without unrealistic over-prediction). With the goal of selecting parameters for two scenarios of regional susceptibility maps, PLR allows us to determine the balance between TPR and FPR for one method with different input parameters.
Citation: https://doi.org/10.5194/nhess-2024-141-AC1
-
RC2: 'Comment on nhess-2024-141', Anonymous Referee #2, 21 Nov 2024
In this study, the authors conduct a detailed regional analysis of landslide mobility in the context of the events triggered by Hurricane Maria in 2017, specifically focusing on (part of) Puerto Rico. Their investigation builds upon past landslide data, slope stability analysis, and geological and terrain data. The authors employed a dual approach to evaluate landslide runout (shorter runout landslides and more extended runout within channels). Furthermore, they incorporated a growth function to further consider input to debris flows based on topographic parameters.
The analyses are thorough and presented clearly. The manuscript is also well-written. The topic itself is relevant and completely fits the scope of NHESS. This is why I would like to recommend it for publication with very minor revisions.
Here are my specific points to consider:- I understand that the potential landslide source areas are extracted from the literature. Still, I think it could be helpful to briefly give more details, perhaps in a paragraph, on how those potential source areas are calculated. This is to give the reader a bit more context without the need to go further to another publication.
Regarding the format, I believe there is a lot of potential to improve the illustrations. I understand it is a matter of taste, but with such quality of analysis, the figures do not do justice. Some of them have low resolution or are a bit convoluted. I would suggest using a similar illustration style (especially the maps). Specific comments are below:
- I do not see the purpose of Figure 2. It would be helpful if you could add more details or simply remove it and instead build the same connection you want to illustrate in Figure 5. That would also save a Figure since you already have quite a lot.
- At the same time, the resolution of Figures 5, 6, and 7 urgently needs to be increased.
- In the legend of Fig 11, there is some underlined text that I suppose was not intended.
- I would suggest removing the word ‘perfect classification’ from Figure 15.
- There is a type in the first table. It should be Table 1 instead.
- Perhaps Fig 16 and 17 could be combined with a rectangle indicating the area being zoomed in.
Citation: https://doi.org/10.5194/nhess-2024-141-RC2 -
RC3: 'Comment on nhess-2024-141', Anonymous Referee #3, 23 Nov 2024
Overall
This research is attempting to develop a model that combines the model for the landslide initiation and the sediment flow down as debris flow. In addition, two models are combined for the debris flow, including mobilization of landslide, in terms of the difference in topographical conditions, one for open slope and the other for channel. Moreover, both models are relatively simple and have great advantages, such as applicability to a wide area. As far as the reviewer knows, a similar approach has never been seen, so this is a highly novel research.
However, I consider that the paper is very long, does not focus on the novel aspects mentioned above, and the purpose, novelty, and important findings of the research are extremely difficult to recognize. I consider that the authors will make major revisions before accepting the paper for the journal.
1．Clarification of the significance of model coupling
The reviewer understands that the concept presented in Chapter 2 is the most important point of this study. However, it is difficult to say that the effectiveness of this concept has been sufficiently demonstrated and examined.
First, regarding the discussion section in Chapter 7, most of it (specifically Sections 7.2 and 7.3) is a discussion of the performance of individual models, which is not the main issue of this study. I think that these sections may blur the focus and mask the significance of this study, so I propose deleting them. Anyway, please comment and consider the significance of the concept presented in Chapter 2 for disaster prediction, if the authors also consider the concept is the most important.
I consider that it is necessary to compare the results of the proposed model with those of the case where the H/L approach or debris flow growth approach is used alone without distinguishing between channel and open slope to be clear the role of model coupling. I also think that it is important to consider how the conditions for distinguishing between channel and open slope affect the results.
If the authors don’t think other parts is more important, I hope the author clearly state it in Introduction.
２．The role of topographic analysis
The reviewer felt that the purpose/role of the topographic analysis in this study was not clear. The reviewer understood that the topographic analysis in this study is a preparatory step for creating a hazard(susceptibility) map, which is necessary to determine several empirical parameters of the proposed model. If this understanding is correct, I would like this point to be clarified. For example, the term “Topographic analysis” in Figure 5 (which I think is an important figure) could be called "Empirical parameters setting through topographic analysis" and the title of Section 4.2 could be "Topographic analysis for empirical parameters setting." I also think that the writing style and structure of Chapter 5 would be reconsider and rewritten to make it easier to read and understand the role of the topographic analysis. I also think that the content of Section 7.1 needs to be reconsidered. In this case, Figure 5 would be revise easier to understand, for example, the linked-model part is set as the main (routine) in the figure, and empirical parameters setting through topographic analysis was added as a sub-part (routine).
On the other hand, if the topographic analysis itself was the purpose of this study, I think it is necessary to clarify in the introduction that there are issues that have not been clarified in previous studies of landslides and debris flow, and that what a kind of data is lacking. In fact, as the authors note in the Discussion section (e.g., 7.2), there is a great deal of prior research, and the reviewers could not consider that the results of the topographic analysis were significantly novel.
3．Clarifying overall model picture
It was very difficult to understand the overall structure of the proposed model. I think that Figure 5 fulfills that role, but it difficult to understand. I made a few comments about this figure in comment 2.
Also, I think it is easier to understand if the relationships among the three models are the same in Figures 2 and 5. Also, it would be easier to understand if it indicated where in the text the methods for each part of the figure are written.
Also, a list of the conditions and coefficients that need to be determined for the terrain classification and each model is helpful to understand overall structure of the proposed model, Moreover. it would be easier for readers to understand if the determination method in this research was organized in the list. It would be very informative for future research if the authors could clarify which of the conditions that need to be determined have the greatest impact.
Minor comments
Fig. 8c I couldn't distinguish between a plot of just the source and a plot of the entire area.
L419 etc. I found “area susceptible to shallow landslide” in several time in this section. However, in the table, the authors noted as “steep slope area”. I hope the authors clarify it.
L429-432 It is hard to understand this part. Please add more explanation.
Citation: https://doi.org/10.5194/nhess-2024-141-RC3
Viewed
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 213 | 77 | 80 | 370 | 6 | 6 |
- HTML: 213
- PDF: 77
- XML: 80
- Total: 370
- BibTeX: 6
- EndNote: 6
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1