Stages of developing a prototype landslide forecasting framework using geotechnical monitoring: A case study from India

Abstract

Landslides have become a major problem in the Darjeeling Himalayas region of India and authorities are seeking ways to reduce the risk of these events through the development of an early warning system. A forecasting framework is the critical part of early warning system, where the occurrence of landslides is predicted using field or remotely based observation. One strategy for predicting landslides is to use rainfall thresholds, but this approach can result in a high number of false alarms. To address this limitation, it is necessary to monitor unstable slopes in real-time using cost-effective methods. In this study, MicroElectroMechanical Systems (MEMS) sensors were used to monitor slopes in the Chibo village of Darjeeling Himalayas and integrated the data with rainfall thresholds to develop a prototype landslide forecasting framework. The results showed that the combination of MEMS sensors and rainfall thresholds is a promising approach which overcomes the limitations of both methods when used separately. © 2023 selection and editorial matter, Askar Zhussupbekov, Assel Sarsembayeva & Victor N. Kaliakin

individual chapters, the contributors.