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Computational methods for simulating soil parameters using electrical resistivity technique

Publication Type : Conference Paper

Publisher : IEEE

Source : 8th International Conference on Computing, Communications and Networking Technologies, ICCCNT 2017, 2017, 8204145

Url :

Campus : Amritapuri

Center : Amrita Center for Wireless Networks and Applications (AmritaWNA)

Verified : Yes

Year : 2017

Abstract : Landslides are environmental disasters that are threat to human life. According to the recent surveys, almost 80% of landslides in India are induced by heavy rainfalls. Heavy rainfall triggers dynamic changes in soil moisture content and pore water pressure, which contributes for slope instability. Therefore monitoring these parameters in large scale is required for providing early-warning of rainfall induced landslides. However, with the current techniques huge cost is involved in monitoring these vital parameters over a large scale. In this paper, we discusses about Electrical resistivity technique, one of the prominent and low cost method used for monitoring soil moisture content over a large scale. Electrical Resistivity (ER) experiments were conducted to observe the credibility of the existing computational methods for simulating soil moisture content from the electrical resistivity measurements of the soil. Regression equations are found from these computational methods to better approximate the soil moisture values from ER measurements. The uncertainty associated with these computational methods were checked using the actual moisture values from the moisture sensor. The regression equations obtained from this experiment can thus be used for simulating moisture values over a large scale in the Munnar landslide prone area if ER measurements are done.

Cite this Research Publication : V. V. Sai and T. Hemalatha, "Computational methods for simulating soil parameters using electrical resistivity technique," 2017 8th International Conference on Computing, Communication and Networking Technologies (ICCCNT), 2017, pp. 1-7, doi: 10.1109/ICCCNT.2017.8204145.

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