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the Creative Commons Attribution 4.0 License.
| 28 Oct 2024
Probabilistic Seismic Landslide Hazard Assessment Considering Different Scenarios of Earthquake and Rainfalls in Bomi, China
Abstract. Probabilistic seismic landslide hazard assessments are critical to infrastructure safety and disaster mitigation in earthquake-prone zones. Previous studies on the probabilistic seismic landslide hazard (PSLH) assessment considered only earthquakes, while rainfall was rarely or not yet considered, which might affect significantly the spatio-temporal pattern of potential seismic landslides. Considering the uncertain features of both earthquake and rainfalls, we developed a novel method for PSLH assessment referring to static factors (geology, topography, and landuse/landcover) and dynamic factors (earthquake and rainfalls), and assessed the PSLH in Bomi, China, which is a strong earthquake-prone zone threatened by heavy rainfalls in the southeast of the Tibet plateau. Firstly, the earthquake parameters under four kinds of earthquake scenarios, being frequent, occasional, rare, and extremely rare, were obtained with the probabilistic seismic hazard analysis method to quantify the effect of future earthquakes. Secondly, we quantified the spatio-temporal distribution of the soil slope saturation with a rainfall infiltration model considering the monthly different rainfalls. Then, considering the different scenarios of both earthquake and rainfall, we assessed in detail the PSLH with a permanent displacement model. The results show that the risky zones of seismic landslide hazards differ significantly in Bomi under different scenarios, where high and extremely high hazard zones concentrate mainly in the south part; and the pattern of seismic landslide hazards changes a lot with monthly differential rainfalls. The method presented in this study is meaningful for the prevention and mitigation of seismic landslides in other mountainous areas threatened by strong earthquakes and suffering from heavy rainfalls.
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RC1: 'Comment on egusphere-2024-2481', Jürgen Mey, 13 Nov 2024
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Review for “Probabilistic Seismic Landslide Hazard Assessment Considering Different Scenarios of Earthquake and Rainfalls in Bomi, China” by Chen Shuai et al.
Landslides are a common phenomenon in mountainous regions. Among the most common triggers of landslides are rainfall and earthquakes. In this manuscript the authors follow an approach that includes rainfall in a probabilistic seismic hazard assessment workflow.
The landslide hazard is categorized based on the permanent seismic displacement, which is a function of the yield acceleration and the peak ground acceleration. In the calculation of the yield acceleration they account for spatial heterogeneity of the rock mass strength by using a scaling factor for the initial yield acceleration. The latter is dependent among others on the water saturation of the subsurface. This in turn is computed with the wetting front depth, which itself is dependent on the rainfall intensity.
They apply their model to Bomi County at the eastern Himalayan syntaxes, a region of strong seismicity and landslide hazard. They compare models that account for rainfall with those that ignore rainfall. They find that the spatiotemporal distribution of rainfall has a substantial impact on the landslide hazard assessment.
Although I see the usefulness of such a model, I have doubts that the used data is sufficient for the task. One striking example is the rainfall data, which relies on a single station. There is no information how the rainfall for the entire county has been derived from it. In addition, how were the mechanical properties determined? There is too few information on the landslide inventory as well. How was the performance of the model evaluated?
I also suggest restructuring the introduction to also include the study area. Furthermore the research question should be clearly formulated in the introduction.
In its current form, the manuscript must be rejected. It would need substantial overhaul to make it ready for publication in NHESS.
Further comments:
Title: In the title you should write “Bomi County” instead of just “Bomi”. After all you did the assessment for the entire county not just for the town.
L30: Please clarify whether these people were all victims to landslides.
L55: “few studies have considered…” references of a few studies needed
L66-67: “…in recent years (JIbson, 1993; Wieczorek et al., 1985) …” if it has become widely used in recent years why not citing more recent studies?
L72: What does CRMSH stand for?
L73: “… 2008 Wenchuan M7.9 earthquake” a reference needed
L74: “.. that the geo-environment characteristics of Bomi are much similar to that of Wenchuan and Ludian” Could you justify this claim somehow? Both, Ludian and Wenchuan are ~800 km away from Bomi.
L95: This should be the first equation because it is the metric you use to define the landslide hazard, right?
L116-123: These lines and equations can be removed because they are not used after all (see comment below).
L124: So you converted the monthly value (mm/month) into m/s?
L131: the variable t has already been defined as rainfall duration in L111.
L138: Study area should go to the introduction.
L148-151: “For example …” It is not clear how this relates to the great earthquake in the previous sentence.
L162 “the slopes in Bomi were divided into five different groups, i.e., Groups 1~5” this is confusing, you divide the lithologies not the slopes.
L165: “The mechanical parameters … are then assigned referring to previous studies (Du et al., 2022).” First of all you write “studies” but give only a single study for reference. Secondly, I checked the study and they used different values for their lithologies, which are also not exactly the same as they occur in Bomi. For example, for loose sediments they use c’ = 25, phi’=24 and gamma=14, whereas you use 17-23, 22-28 and 10-14, respectively. Similar deviations can be observed for the other lithologies as well. How do you come up with these numbers? In general, there is a lack of information how the mechanical properties have been determined.
L165: ”different groups” which ones? Be specific.
L170-172: “Since these parameter …” This is a strong assumption that needs to be discussed.
L175: Table caption: It would help the reader to again write out the names of these parameters here.
Further, start description of the groups with group one on the top.
L177: What radius was used for calculating the relief?
L178: What is tectonic distribution? Do you mean the distribution of faults?
L181: “1:1,000,000 river distribution” reference needed; “using ArcGIS” What exactly did you do?
L187: As stated above there is way too few information regarding this inventory. Reference? How was it created? Looks like the landslides cluster along roads. Is there perhaps an observational bias? How many landslides are there? Which timeframe is considered? How many were triggered by earthquakes, how many by rainfall, and which ones?
L192: How was the rainfall distribution derived from only a single station within the county? There is also a reference needed.
L206-209: Can you give the moment magnitudes that correspond to these scenarios?
L210: Who created the PGA map? If you did it, how? It is not mentioned in the methodology. And then it should go to the results.
L220: Table 2: You list only 12 scenarios with the monthly rainfall intensities but later you present 48 scenarios in Fig.11.
L226: “Higher … “ How did you incorporate historic landslides in the calculation?
L238-243: How do you explain the spatial distribution of hazard zones?
L244: Where are these statistics shown?
L262-263: Here you state that you assume that the saturated hydraulic conductivity is always greater than the rainfall in Bomi. So you only use equation 7, right? Then I suggest removing equations 8 and 9. What value do you assign to t in equation 7?
L292: “is effective in assessing the PSLH in earthquake-prone mountainous” How did you evaluate the effectiveness of your model?
L293: “significantly” Can you show that it is significant in a strictly statistical sense?
L306: “While the zonation map … zonation map.” This statement makes me question the validity of the zonation map. You refer to seismic parameters that are higher in the records than those that correspond to the scenarios in the zonation map. Can you give numbers for both? Which seismic parameters are you referring to?
L333: “details in localized topography, which often has important impacts on the occurrence of seismic landslides” please specify
Figures:
In general I advise to use different colormaps for different things. The chosen red-green colormap is not a good choice, because it excludes every person who is color blind. Moreover, in most of the result maps the colors are practically indistinguishable.
Fig.3: What kind of faults are depicted here? What is the source of the earthquakes -> reference? What does “historic” mean actually? Are these Earthquakes that occurred during the last century?
Fig.5: How was this spatial distribution of rainfall derived? Why does it rain more in the valleys compared to the ranges? I would assume that there is an orographic effect that would lead to the opposite pattern.
Fig.6. You should replace the Chinese scripts with latin ones.
Fig.8: Hard to differentiate the colors. Please give some information regarding the magnitudes of EQ in these scenarios.
Fig.9: I see no change between (a) and (b).
Fig.12: The way you show the hazard is confusing. I would assume that affected area decreases with the hazard level, not the other way around. Since areas with extreme hazard level are also incorporating areas with lower hazard levels, the former should always be smaller than the latter.
J. Mey
Citation: https://doi.org/10.5194/egusphere-2024-2481-RC1
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