Study of rainfall-induced landslide using a self-developed tilt monitoring system: a physical and numerical modelling approach

Landslides in northern India are a frequently occurring risk during the rainy season resulting in human, animal, and property losses as well as obstructing transportation facilities. Usually numerical and analytical approaches are applied towards the prediction and monitoring of landslide but the unpredictable nature of rainfall induced landslide limits these methods. Sensor based monitoring proved to be an accurate and reliable method in real time and it also collect accurate and site-specific required data for further investigation with numerical and analytical approach. In this study, a self-developed low-cost slope monitoring system including MEMS-based tilt and moisture sensors were used to monitor variation in tilt deformation and water content. A physical slope model was also prepared to test the monitoring system in a real scenario. A landslide occurred at Kotrupi village in Mandi district of Himachal Pradesh, India, was chosen for the modelling to investigate the failure mechanism. Further numerical modelling was conducted to investigate the slope's failure mechanism and for validation purposes, allowing for the development of feasible strategies for the future study of various landslides and the mitigation of their effects. The results show that the developed system is very effective in monitoring rainfall-induced landslides as it monitors the gradual and sudden movement effectively. The tilt angle records the deviation in terms of angle with a least count of 0.01 degree and the moisture content was recorded in terms of percentage with a least count of 1. Numerical analysis highlighted the factor of safety before rainfall was 1.045 and after rainfall it decreased to 0.670 validating that the rainfall was the triggering cause of the slope failure. This study explains the mechanism behind the landslide and it can be helpful in monitoring the slope in order to enable the implementation of preventative actions that will mitigate its impact.