Correlations for Laboratory Test Parameters

Ameratunga, Jay; Sivakugan, N.; Das, Braja M.

doi:10.1007/978-81-322-2629-1_3

Cited by 2 publications

(3 citation statements)

References 35 publications

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“…This also agrees with the type of landslides often triggered by short, heavy rainfall events causing a rapid increase in pore pressure (Crosta, 1998). Such landslides are characterized by small and shallow, slope-parallel failure planes (depth of 0.3-2 m; Anderson and Sitar, 1995). The displaced material, by means of processes of static liquefaction and rapid reduction of shear strength in undrained conditions, develops into flows that spread downward (Anderson and Sitar, 1995;Wang and Sassa, 2003).…”

Section: Discussionsupporting

confidence: 79%

“…Such landslides are characterized by small and shallow, slope-parallel failure planes (depth of 0.3-2 m; Anderson and Sitar, 1995). The displaced material, by means of processes of static liquefaction and rapid reduction of shear strength in undrained conditions, develops into flows that spread downward (Anderson and Sitar, 1995;Wang and Sassa, 2003). This type of landslide is described by Hungr et al (2014) as a debris avalanche.…”

Section: Discussionmentioning

confidence: 99%

“…The dry unit weight ranges from 14.3 to 14.9 kN m −3 . No geotechnical laboratory tests are available for the alluvial deposits; however, they show very gentle slopes generally not prone to landslides; the cohesion and friction angle values were therefore assumed based on literature values (Ameratunga et al, 2016;Aristizábal, 2013;Aristizábal et al, 2015;Geotechdata, 2013).…”

Section: Data and Proceduresmentioning

confidence: 99%

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Probabilistic landslide susceptibility analysis in tropical mountainous terrain using the physically based r.slope.stability model

Palacio

Mergili

Aristizábal

2020

Nat. Hazards Earth Syst. Sci.

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Abstract. Landslides triggered by rainfall are very common phenomena in complex tropical environments such as the Colombian Andes, one of the regions of South America most affected by landslides every year. Currently in Colombia, physically based methods for landslide hazard mapping are mandatory for land use planning in urban areas. In this work, we perform probabilistic analyses with r.slope.stability, a spatially distributed, physically based model for landslide susceptibility analysis, available as an open-source tool coupled to GRASS GIS. This model considers alternatively the infinite slope stability model or the 2.5-D geometry of shallow planar and deep-seated landslides with ellipsoidal or truncated failure surfaces. We test the model in the La Arenosa catchment, northern Colombian Andes. The results are compared to those yielded with the corresponding deterministic analyses and with other physically based models applied in the same catchment. Finally, the model results are evaluated against a landslide inventory using a confusion matrix and receiver operating characteristic (ROC) analysis. The model performs reasonably well, the infinite slope stability model showing a better performance. The outcomes are, however, rather conservative, pointing to possible challenges with regard to the geotechnical and geo-hydraulic parameterization. The results also highlight the importance to perform probabilistic instead of – or in addition to – deterministic slope stability analyses.

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