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Erschienen in: Environmental Earth Sciences 1/2013

01.09.2013 | Original Article

Simple and multiple regression models for relationship between electrical resistivity and various soil properties for soil characterization

verfasst von: Fahad Irfan Siddiqui, Syed Baharom Azahar Bin Syed Osman

Erschienen in: Environmental Earth Sciences | Ausgabe 1/2013

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Abstract

Precise determination of engineering properties of soil is essential for proper design and successful construction of any structure. The conventional methods for determination of engineering properties are invasive, costly and time-consuming. Electrical resistivity survey is an attractive tool for delineate subsurface properties without soil disturbance. Reliable correlations between electrical resistivity and other soil properties will enable us to characterize the subsurface soil without borehole sampling. This paper presents the correlations of electrical resistivity with various properties of soil. Soil investigations, field electrical resistivity survey and laboratory electrical resistivity measurements were conducted. The results from electrical resistivity tests (field and laboratory) and laboratory tests were analyzed together to understand the interrelation between electrical resistivity and various soil properties. The test results were evaluated using simple and multiple regression analysis. From the data analysis, significant quantitative and qualitative correlations have been obtained between resistivity and moisture content, friction angle and plasticity index. Weaker correlations have been observed for cohesion, unit weight of soil and effective size (D 10).

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Metadaten
Titel
Simple and multiple regression models for relationship between electrical resistivity and various soil properties for soil characterization
verfasst von
Fahad Irfan Siddiqui
Syed Baharom Azahar Bin Syed Osman
Publikationsdatum
01.09.2013
Verlag
Springer Berlin Heidelberg
Erschienen in
Environmental Earth Sciences / Ausgabe 1/2013
Print ISSN: 1866-6280
Elektronische ISSN: 1866-6299
DOI
https://doi.org/10.1007/s12665-012-2122-0

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