Influence of earthquakes on the stability of slopes

Hack, H.R.G.K.; Alkema, D.; Kruse, G.A.M.; Leenders, Noud; Luzi, Lucia

doi:10.1016/j.enggeo.2006.12.016

Cited by 65 publications

(26 citation statements)

References 24 publications

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“…Normally, earthquake-induced landslides happen due to an increase in destabilizing forces and because of ground acceleration due to propagation of seismic waves, or decrease in soil strength. Soil strength reduction can occur due to an increase in pore water pressure caused by cyclic loading especially in loose unconsolidated deposits, or a decrease in inter-particle bonding because of ground displacements due to seismic waves (Hack et al, 2007). In several studies, to consider the contribution of earthquakes to the landslide occurrence, peak ground acceleration (PGA) has been used as a landslide triggering factor for landslide hazard evaluation (e.g., Bai et al, 2012;Xu et al, 2012b).…”

Section: Seismicitymentioning

confidence: 99%

A new hybrid model using step-wise weight assessment ratio analysis (SWARA) technique and adaptive neuro-fuzzy inference system (ANFIS) for regional landslide hazard assessment in Iran

Dehnavi

Aghdam

Pradhan

et al. 2015

CATENA

243

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Keywords: Landslide susceptibilityStep-wise weight assessment ratio analysis (SWARA) method Adaptive neuro-fuzzy inference system (ANFIS) Geographical information system (GIS) Remote sensing Iran In recent years, Iran has experienced many landslides due to high tectonic activity, and a variety of geological and climatic conditions. This paper proposes a novel hybrid model based on step-wise weight assessment ratio analysis (SWARA) method and adaptive neuro-fuzzy inference system (ANFIS) to evaluate landslide susceptible areas using geographical information system (GIS). At first, based on an inventory map, landslide locations were randomly divided into two parts, 70% of which were used for generating the landslide hazard map and 30% of which were used for the validation of the model. Then, twelve landslide predisposing factors, such as lithology, slope angle, slope aspect, plan curvature, profile curvature, altitude, distance to streams, distance to faults, distance to roads, land use, seismicity, and rainfall were considered for the analysis. All the factors were then weighted by the SWARA method. Considering the nature of predisposing factors, they were split into two groups, factors with discrete data and factors with continuous data. For factors with discrete data, the SWARA method was used for final weight of each class, and for factors with continuous data, results related to the center of each class were obtained from the SWARA method. Subsequently, AFNIS was used to obtain weight of each value. All the values obtained from the model were then used to generate the landslide hazard map of the study area. Finally, the landslide hazard map was validated by receiver operating characteristics (ROC) using both success rate curve and prediction rate curve. 70% of observed landslides were used for the former while the remaining was used for the latter. The validation results showed that the area under the success rate curve and prediction rate curve (AUC) are 0.84 and 0.80 respectively. Additionally, the prediction performance of the SWARA method for landslide hazard mapping was investigated and the results were compared with those obtained from the proposed model. The comparison revealed that the developed model has better prediction ability for landslide hazard assessment. The results also indicated that the proposed model used in this study produced satisfactory and reliable landslide hazard map, which can be used for preliminary land use and infrastructure planning in Iran.

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Section: Seismicitymentioning

confidence: 99%

A new hybrid model using step-wise weight assessment ratio analysis (SWARA) technique and adaptive neuro-fuzzy inference system (ANFIS) for regional landslide hazard assessment in Iran

Dehnavi

Aghdam

Pradhan

et al. 2015

CATENA

243

View full text Add to dashboard Cite

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“…Those based on: (1) the limit equilibrium method (LEM) [9][10][11]23]; (2) the limit analysis method [6,24] and; (3) the finite element method (FEM) [25,26]. Other methods of analysis, like the finite difference method [27,28], distinct element method [29], probability assessment [30,31] are also used in current slope stability analyses. Duncan [32] provides a comprehensive review for two dimensional (2D) and three dimensional (3D) LEM and FEM estimates of slope stability, and therefore the review of literature herein will be referring to more recent publications (post 1996).…”

Section: Previous Studiesmentioning

confidence: 99%

Limit analysis solutions for three dimensional undrained slopes

Li¹,

Merifield²,

Lyamin³

2009

Computers and Geotechnics

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“…Moreover, rockfalls and other landslides are one of the main secondary effects of large earthquakes (Keefer, 1984;Rodrıguez et al, 1999;Hack et al, 2007). Rockfall hazard zoning is therefore important for land-use planning, especially in seismic areas having steep slopes.…”

Section: Introductionmentioning

confidence: 99%