Application of a 3D deterministic model for predicting shallow loess landslide stability

XIN Xing; ZHANG Fan-yu

doi:10.13374/j.issn2095-9389.2018.04.002

Volume 40 Issue 4

Apr. 2018

Turn off MathJax

Article Contents

Article Navigation > Chinese Journal of Engineering > 2018 > 40(4): 397-406

XIN Xing, ZHANG Fan-yu. Application of a 3D deterministic model for predicting shallow loess landslide stability[J]. Chinese Journal of Engineering, 2018, 40(4): 397-406. doi: 10.13374/j.issn2095-9389.2018.04.002

Citation:

XIN Xing, ZHANG Fan-yu. Application of a 3D deterministic model for predicting shallow loess landslide stability[J]. Chinese Journal of Engineering, 2018, 40(4): 397-406. doi: 10.13374/j.issn2095-9389.2018.04.002

Citation:

PDF( 830 KB)

Application of a 3D deterministic model for predicting shallow loess landslide stability

doi: 10.13374/j.issn2095-9389.2018.04.002

XIN Xing^1,2,
ZHANG Fan-yu^{1,2
,
,}

1) Key Laboratory of Mechanics on Disaster and Environment in Western China, Ministry of Education, Lanzhou University, Lanzhou 730000, China;
2) School of Civil Engineering and Mechanics, Lanzhou University, Lanzhou 730000, China

Received Date: 2017-04-07

Abstract

Abstract

In the loess plateau, shallow loess landslides are especially widespread and frequent geological disasters, causing serious casualties as well as huge property damage. Although two-dimensional deterministic models are widely applied to assess the stability of shallow landslides, they could not sufficiently consider the three-dimensional spatial variation of geotechnical property, layering configurations and groundwater. It might not conform with the actual situation of slope stability. Therefore, the three-dimensional deterministic model with considering complicated slope situation has the great significance to acquire the results that are more accordant with the actual situation. At the same time, it will exercise a profound and far-reaching influence to effectively mitigate landslide disasters. This paper takes the three-dimensional deterministic model Scoops3D to evaluate its adaptation and reliability of predicting shallow loess landslide stability. Firstly, the sensitivity analysis of model calculating parameters indicates that the most influential parameters on accuracy of safety factor are cohesive force, sliding direction of visual angle and the weight of grids, so it could guide to acquire the detail key input parameters. Then, the different resolution digital elevation models (DEMs) and geotechnical parameters are selected and used to predict the stability of shallow loess landslides in the typical gully and ridge physiographic region by using the Scoops3D. Comparing the calculated results with the detail inventory of point landslides and facial shape landslides shows that this model has a high accuracy in predicting shallow landslide stability. At the same time, the inventory of point landslides may be more suitable to model verification than facial shape landslides. Finally, the confusion matrix and the success rate curve are used to examine the reliability of predicted results that based on different resolution DEMs. The results prove that this model has a good adaptation to predict the stability of shallow loess landslides in the selected study area. Meanwhile, it could obtain reliable prediction accuracy with the high-resolution DEM data.
- shallow loess landslide,
- three-dimensional deterministic model,
- stability prediction,
- resolution of digital elevation models,
- precision validation,
- Scoops3D

FullText(HTML)

References(22)

References

[1]	Zhang F Y, Chen W W, Liu G, et al. Relationships between landslide types and topographic attributes in a loess catchment, China. J Mountain Sci, 2012, 9(6):742
[2]	Zhou J X, Zhu C Y, Zheng J M, et al. Landslide disaster in the loess area of China. J Forestry Res, 2002, 13(2):157
[5]	Zhang F Y, Wang G H, Kamai T, et al. Effect of pore-water chemistry on undrained shear behavior of saturated loess. Q J Eng Geol Hydrogeol, 2014, 47(3):201
[6]	Zhang F Y, Wang G H, Kamai T, et al. Undrained shear behavior of loess saturated with different concentrations of sodium chloride solution. Eng Geol, 2013, 155:69
[9]	Guzzetti F, Reichenbach P, Ardizzone F, et al. Estimating the quality of landslide susceptibility models. Geomorphology, 2006, 81(1-2):166
[10]	Baeza C, Corominas J. Assessment of shallow landslide susceptibility by means of multivariate statistical techniques. Earth Surf Processes Landforms, 2001, 26(12):1251
[11]	Montgomery D R, Dietrich W E. A physically-based model for the topographic control on shallow landsliding. Water Resour Res, 1994, 30(4):1153
[12]	Godt J W, Baum R L, Savage W Z, et al. Transient deterministic shallow landslide modeling:requirements for susceptibility and hazard assessments in a GIS framework. Eng Geol, 2008, 102(3-4):214
[13]	Wu W M, Sidle R C. Application of a distributed shallow landslide analysis model (dSLAM) to managed forested catchments in Oregon, USA//Proceedings of Rabat Symposium S6. Rabat, 1997:213
[14]	Iverson R M. Landslide triggering by rain infiltration. Water Resour Res, 2000, 36(7):1897
[16]	Reid M E, Christian S B, Brien D L, et al. Scoops3D——software to analyze three-dimensional slope stability throughout a digital landscape[J/OL]. U. S. Geological Survey Techniques and Methods (2017-01-11)[2017-04-07]. https://pubs.usgs.gov/tm/14/a01/
[17]	Alvioli M, Raum R L. Parallelization of the TRIGRS model for rainfall-induced landslides using the message passing interface. Environ Modell Softw, 2016, 81:122
[18]	Brien D L, Reid M E. Modeling 3-D slope stability of coastal bluffs using 3-D ground-water flow, southwestern seattle, Washington[J/OL]. Scientific Investigations Report (2012-02-10)[2017-04-07]. https://pubs.er.usgs.gov/publication/sir20075092
[19]	Reid M E, Sisson T W, Brien D L. Volcano collapse promoted by hydrothermal alteration and edifice shape, Mount Rainier, Washington. Geology, 2001, 29(9):779
[20]	Hungr O. An extension of Bishop's simplified method of slope stability analysis to three dimensions. Geotechnique, 1987, 37(1):113
[21]	Reid M E, Christian S B, Brien D L. Gravitational stability of three-dimensional stratovolcano edifices. J Geophys Res Solid Earth, 2000, 105(B3):6043
[22]	Teixeira M, Bateira C, Marques F, et al. Physically based shallow translational landslide susceptibility analysis in Tibo catchment, NW of Portugal. Landslides, 2014, 12(3):455
[24]	Zhang F Y, Pei X J, Chen W W, et al. Spatial variation in geotechnical properties and topographic attributes on the different types of shallow landslides in a loess catchment, China. Eur J Environ Civil Eng, 2014, 18(4):470
[26]	Borga M, Fontana G D, Gregoretti C, et al. Assessment of shallow landsliding by using a physically based model of hillslope stability. Hydrol Processes, 2002, 16(14):2833
[27]	Claessens L, Heuvelink G, Schoorl J, et al. DEM resolution effects on shallow landslide hazard and soil redistribution modeling. Earth Surf Processes Landforms, 2005, 30(4):461
[29]	Van Weste J C, Rengers N, Soeters R. Use of geomorphological information in indirect landslide susceptibility assessment. Nat Hazards, 2003, 30(3):399
[31]	Fawcett T. An introduction to ROC analysis. Pattern Recognit Lett, 2006, 27(8):861