the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Characteristics and RISM of sliding flow landslides triggered by prolonged heavy rainfall in the loess area of Tianshui, China
Jianqi Zhuang
Jianbing Peng
Chenhui Du
Yi Zhu
Jiaxu Kong
Abstract. Shallow loess landslides induced by prolonged heavy rainfall are common in loess dominated areas and often result in property loss, human casualties, and sediment pollution. Building a suitable prediction model for shallow landslides in loess areas is critical for landslide mitigation. In 2013, prolonged heavy rains from July 19th to the 25th triggered shallow loess landslides in Tianshui, China. The “7.25 loess landslides” were used as a case study for this current study. Landslide data, along with the characteristics of the loess shallow landslides were obtained through multiple field investigations and remote sensing interpretations. The “7.25 loess landslides" demonstrated clustering, high density, small areas, and long travel distance. The depth of the sliding surface correlates with the saturated layer (i.e., liquid limited water content) arising from rainfall infiltration, with a sliding depth that is typically less than 2 m and is negatively correlated with the slope. Based on the common characteristics of shallow loess landslides, the mechanisms involved in the sliding flow landslide are proposed. The Revised Infinite Slope Model (RISM) was proposed using equal differential unit method and corrected the deficiency that the safety factor increases with the slope increasing when the slope is larger than 50° calculated using the Taylor slope infinite model. The relationship between the critical depth and the slope of the shallow loess landslide was determined and combined with the characteristics of rainfall infiltration. The intensity-duration (I-D) prediction curve of the rainfall-induced shallow loess landslides under different slopes was constructed and can be used in forecasting regional shallow loess landslides. Additionally, the influence of loess strength on the shallow loess landslide stability has been analyzed. The shallow loess landslide stability responds to slope and cohesion but is not sensitive to the internal friction angle.
Jianqi Zhuang et al.
Status: final response (author comments only)
-
RC1: 'Comment on nhess-2022-135', Anonymous Referee #1, 03 Jun 2022
The present study aims to studying prediction model for the shallow loess landslides events which is frequency occurrence in loess area due to prolonged heavy rainfall. The landslide data, along with the characteristics of the loess shallow landslides were obtained through multiple field investigations and remote sensing interpretations, and then the mechanisms involved in the sliding flow landslide are proposed which is very useful for comprehensive study shallow landslide mechanism.
The outstanding wok of the manuscript is a new Revised Infinite Slope Model (RISM) was proposed using equal differential unit method and corrected the deficiency that the safety factor increases with the slope increasing when the slope is larger than 50° calculated using the Taylor slope infinite mode which is an innovative work. Meanwhile, the intensity-duration (I-D) prediction curve of the rainfall-induced shallow loess landslides under different slopes was constructed combined with the characteristics of rainfall infiltration and RISM, it is the first time propose the intensity-duration (I-D) prediction curve based on physical method.
The manuscript structure is reasonable and readable, and the RISM and prediction model have reference value for the research of shallow landslides. And the manuscript will be attract more read and cited. But there is some information should be added before published, I give the minor revise.
1) the manuscript title is not suitable, and the manuscript title should contain the key words: prediction model etc. e.g., the title can be revised to: A novel prediction method of shallow landslide in loess area based on RISM, a “7.25” loess sliding-flow landslide event in 2013 in Tianshui, China case study.
2) Literatures seems to be extensive. Some recent research on shallow landslides, are suggested to be incorporated and supplemented. For example:
Fatma Keles and Hakan A. Nefeslioglu. Infinite slope stability model and steady-state hydrology-based shallow landslide susceptibility evaluations: The Guneysu catchment area (Rize, Turkey), CATENA, 2021.
Medina V et al. Fast physically-based model for rainfall-induced landslide susceptibility assessment at regional scale. CATENA, 2021.
3) the shallow loess landslide event name is not the same, e.g., “7.25 loess landslides” is used in the abstract, and “7.25” loess sliding-flow landslide events is used in text, please make it unified.
4) Line 85, In Section Introduction, please focus on scientific issues clearly and work to solve these problems well. This section needs definitely gives the research gap and objective about your work.
5) Do the earthquakes and symbols in Figure 1 represent the earthquake magnitude? If so, please add their units “Ms”.
6) English requires proofread by native speakers.
Citation: https://doi.org/10.5194/nhess-2022-135-RC1 - AC1: 'Reply on RC1', J.Q. Zhuang, 08 Oct 2022
-
RC2: 'Comment on nhess-2022-135', Anonymous Referee #2, 07 Sep 2022
The present study aims to improve prediction model for the shallow loess landslides induced by prolonged heavy rainfall.
The outstanding work is the improvement of the Taylor slope infinite model, based on equal differential unit method, permitting to correct the error when the safety factor increases with the increased slope when the slope is larger than 50°. Moreover, the intensity duration (I-D) prediction curve is proposed for the shallow loess landslides, considering the characteristics of rainfall infiltration, and different slopes.
But several misunderstanding are encountered in this paper:
- the study is focused on the development of RISM model, for a better estimation of safety factor for slope higher than 50°. However, as seen from field data (in figure 7), all landslides are triggered in slopes lower than 35°. In that way, we do not really understand why the development of this model can help in quantifying the stability of slope in this context.
- Moreover, the validation of the approach (notably the I-D curve for different slopes) is not realised, as the I-D curves for different slopes are not tested in real case for all landslides.
- Several key information and references are missing, such as: the methodology for obtaining the landslide’s map; the justification about how the 89 studied landslides are representative of the 45 000 landslides; the initial I-D curve that has been used in this study.
Based on these main elements, I suggest to reject the manuscript.
You can also find below some additional comments:
- 3, Line 89 “7.25” loess sliding-flow landslide events in Tianshui Gansu province : please define the meaning of “7.25”, otherwise you have to add the reference to this.
- Figure 1 is not a geomorphological nor geological map; please put elements concerning these 2 features ; moreover, earthquake location is not usefull to this paper, as the study works on landslides induced by heavy precipitations, and not by earthquake.
- I suggest to dedicate paragraph 2 to geological, geomorphological, and climate characteristics ; as the threshold of these landslides is heavy precipitation, I recommend to detail the climate description in a sub-paragraph 2.2 (subparagraph 2.1 could be geological and geomorphological characteristics) ; finally I suggest to move 2.2 to paragraph 3, as it concerns landslides features.
- I think it is necessary to detail input data and the processes to obtain landslides maps, with some zoom on figure 2.
- 7, table 2 : the term “area” is not appropriate ; you can use “surface area”
- 10 Line181 : you have to indicate and discuss whether these 89 landslides are statistically representative of the 47 005 landslides ; you also have to precise the characteristics of the landslide you consider for obtaining the depth of the landslide.
- figure 7 is confusing, as slope and surface areas are in the same graph. 2 separate graphs might be better
- 11, line 200 : it is necessary to provide details and possible explanation about “a certain depth of loess becoming close to liquid limit water content” : which depth? Depending on what?
- 11 line 209 : please provide references concerning the depth of shallow landslides in loess.
- P12 line 214 : it is mentioned that “loess landslide transformation to mudflows occur most often on slopes of 25 – 45°” ; why is it different from the results shown on figure 7? Please explain.
- 12 line 220 ; provide reference of Taylor;
- 12 line 222 ; the length of the body is b, not l
- 12 figure 9 ; I don’t understand the different directions of arrows designing the flow lines ?
- Fig 10 : how do you chose the value c’ phi’, gsat ? for high slopes, I am not sure that such value can be found in the field
- p15, line 292 : please provide some details or references on loess test results ; the figure 13 doesn’t provide these elements
- 15, line 298 : it is necessary to plot this law on figure 13
- 17, figure 14 : we don’t know what is Yan’an “7.13” group shallow landslide . Which are the values of the characteristics used here (C, phi, rainfall events, slopes ….)? more generally, how are constructed these curves ? is it still the parameters c, phi, … from figure 10 that are considered?
- I don’t see here really validation of the model or approach ; you could apply this I-D curve on the all area of study, with considering for each local area or pixel I-D curve, considering local parameters. I don’t understand how you can consider the “7.25 loess sliding-flow events” as a unique point on your analysis.
- 18, figure 15 : legends of the curves are missing, we have no information on them
- 18, paragraph 5.2 : why this part is within the discussion paragraph ?
- As a general comment, the discussion is not really realised.
- 18 Figure 16 : as figure 7, the figure is confusing ; it is better to provide One graph for each parameter;
- 18, line 349 : there are errors in internal friction angle, expressed in kPa!
The paper requires proofread by English native speakers, as it encounters several English mistakes or inadequate words, as well as sentences wrong formulation. Indeed, several sentences are not clear; for instance:
- 1, line 13
- 1, lines 16 to 18 : sentence too long
- 3, line 95 : you mean “the elevation of the study area” ? please check
- 17, line 331 : non comprehensive sentence
- 17, line 333, 334 : I don’t understand
Citation: https://doi.org/10.5194/nhess-2022-135-RC2 - AC2: 'Reply on RC2', J.Q. Zhuang, 08 Oct 2022
Jianqi Zhuang et al.
Jianqi Zhuang et al.
Viewed
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 352 | 118 | 12 | 482 | 2 | 2 |
- HTML: 352
- PDF: 118
- XML: 12
- Total: 482
- BibTeX: 2
- EndNote: 2
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1