Abstract
Studies on rainfall-induced landslides are essential for protecting the lives and property in hilly regions. Augmented numerical investigation considering geotechnical, geological, and environmental parameters of the slope for the past landslides and potential slip surfaces helps in identifying appropriate triggering mechanisms and preventive measures. In this work, numerical modelling was carried out for predicting the time of landslide occurrence of a shallow landslide based on the laboratory estimated soil water characteristic curve (SWCC) data, net rainfall infiltration, runoff, and geological characteristics of the study area. The accurate estimation of the SWCC was vital in the back-analysis of a landslide as SWCC directly governs the hydraulic and shear strength characteristics of the unsaturated slope. Instantaneously measured SWCC by the sensors severely overestimated the suction values for a given water content for the studied soil at different compaction densities. The back-analyzed rainfall-induced slope stability analysis of the case study showed that the estimated factor of safety variation with time by using the conventional SWCC estimation was inconsistent with the observed time of failure. A laboratory method was proposed to evaluate “equilibrium SWCC” data to account for the hydraulic equilibrium between the suction sensor and the field soil. The equilibrium SWCC data accurately predicted the time of landslide occurrence and slip surface. Further, the present study also highlighted the significance of the field density and net rainfall infiltration, considering climatic data, on forensic investigations through sensitivity analysis.
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The data and models generated during the study are available from the corresponding author upon reasonable request.
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Das, P., Patwa, D., G., V. et al. Influencing factors on the simulation of rainfall-induced landslide prediction based on case study. Bull Eng Geol Environ 81, 194 (2022). https://doi.org/10.1007/s10064-022-02682-3
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DOI: https://doi.org/10.1007/s10064-022-02682-3