Version 2
: Received: 27 February 2020 / Approved: 27 February 2020 / Online: 27 February 2020 (16:04:46 CET)
How to cite:
Singh, V. A Physical and Numerical Based Model for Early Prediction of Landslides Using Wireless Sensor Network. Preprints2020, 2020020096. https://doi.org/10.20944/preprints202002.0096.v2
Singh, V. A Physical and Numerical Based Model for Early Prediction of Landslides Using Wireless Sensor Network. Preprints 2020, 2020020096. https://doi.org/10.20944/preprints202002.0096.v2
Singh, V. A Physical and Numerical Based Model for Early Prediction of Landslides Using Wireless Sensor Network. Preprints2020, 2020020096. https://doi.org/10.20944/preprints202002.0096.v2
APA Style
Singh, V. (2020). A Physical and Numerical Based Model for Early Prediction of Landslides Using Wireless Sensor Network. Preprints. https://doi.org/10.20944/preprints202002.0096.v2
Chicago/Turabian Style
Singh, V. 2020 "A Physical and Numerical Based Model for Early Prediction of Landslides Using Wireless Sensor Network" Preprints. https://doi.org/10.20944/preprints202002.0096.v2
Abstract
Landslides are a frequent and recurrent problem in hilly regions of India and predicting them is always a challenging task. In this paper, an attempt was made to deal with this problem using advanced physical and numerical modeling methods. Detailed understanding of the initial slope failures is very interesting, and challenging at the same time, in the design and development of wireless sensor network based on early warning of landslide monitoring. A small scale physical model was developed to assess the instability through a sensor network with variable rain fall intensity. This was achieved by increasing the simulated rain water flow intensity in different time spans (dry condition, at t=0 to t= 30 min, 0.5 mm/min at t=30 to t= 60 min, 0.75 mm/min at t=60 to t=91 min and 1 mm/min at t=91 to t= 120 min). The water level and movement in the slope was recorded by rainfall sensor, vibration sensor, soil moisture sensor and a digital camera. The following changes were observed during the slope failure: a) movement of small particles at top of the slope; b) initial failure of medium size soil particle; c) scouring of soil mass; d) whole slope collapse. The obtained results clearly indicated the superiority and effectiveness of the proposed system in providing a factor of safety for the progressive slope.
Keywords
Landslides; Factor of Safety(FoS); Wireless Sensor Network; Slope Stability
Subject
Environmental and Earth Sciences, Geophysics and Geology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Commenter: Vinay Singh
Commenter's Conflict of Interests: Author