Prediction of rainfall-induced landslide movements in the presence of stabilizing piles

Among the different techniques usually employed to stabilize landslide bodies, the use of one or more rows of piles firmly embedded in the stable portion of the slope is commonly considered a reliable and effective measure. Nevertheless, a landslide may still be reactivated by an increase in the groundwater level due to rainfall. In this context, a novel method is proposed in the present study for a preliminary evaluation of the rainfall-induced movements of landslides in the presence of stabilizing piles. This method uses a water balance equation to evaluate the groundwater level changes due to rainfall, and the motion equation to relate these changes to landslide displacements. The piles contrast the landslide movements by a passive resistance force the value of which depends on the pile-soil failure mode and pile arrangement. The proposed method appears attractive from an engineering viewpoint, since it can be readily implemented in a common electronic sheet and requires few parameters as input data. Most of these parameters can be obtained from conventional geotechnical tests, whereas the remaining ones should be calibrated on the basis of available measurements of rainfall, groundwater level and soil displacement. After performing this parameter calibration, the method may be employed for predictive purposes to relate future landslide movements to expected rainfall scenarios. The predictive capability of the present approach is assessed by comparing the results with those observed in a published case study concerning a landslide body periodically reactivated by rainfall, in which a row of stabilizing piles was installed.

Automated summary

A novel method is proposed in this study to evaluate rainfall-induced movements of landslides in the presence of stabilizing piles, using a water balance equation and motion equation. The method is attractive from an engineering perspective, as it can be readily implemented and requires few input parameters, making it suitable for predicting landslide movements in relation to rainfall scenarios.