Forewarning of Debris flows using Intelligent Geophones

Landslides are one of the major catastrophic disasters that cause significant damage to human life and civil structures. Heavy rainfall on landslide prone areas can lead to most dangerous debris flow, where the materials such as mud, sand, soil, rock, water and air will move with greater velocity down the mountain. This sudden slope instability can lead to loss of human life and infrastructure. According to our knowledge, till now no one could identify the minutest factors that lead to initiation of the landslide. In this work, we aim to study the landslide phenomena deeply, using the landslide laboratory set up in our university. This unique mechanical simulator for landslide initiation is equipped with the capability to generate rainfall, seepage, etc., in the laboratory setup. Using this setup, we aim to study several landslide initiation scenarios generated by varying different parameters. The complete setup will be equipped with heterogeneous sensors such as rain gauge, moisture sensor, pore pressure sensor, strain gauges, tiltmeter, inclinometer, extensometer, and geophones. Our work will focus on the signals received from the intelligent geophone system for identifying the underground vibrations during a debris flow. Using the large amount of signals derived from the laboratory set up, we have performed detailed signal processing and data analysis to determine the fore warning signals captured by these heterogeneous sensors. Detailed study of these heterogeneous signals has provided the insights to forewarning the community based on the signals generated during the laboratory tests. In this work we will describe the details of the design, development, methodology, results, inferences and the suggestion for the next step to detect and forewarn the students. The response of intelligent geophone sensors at the time of failure, failure style and subsequent debris flow for heterogeneous soil layers were studied, thus helping in the development of fore warning systems for debris flows.