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Probabilistic identification of contaminated soils using resistivity piezocone penetration tests
The identification of contaminated soils has gained increasing interest over the decades in the geoenvironmental issues. In this study, a probabilistic method based on the geostatistics and the reliability-based analysis is performed on the resistivity piezocone penetration testing data to evaluate the spatial distribution of the contaminants including the heavy metal ions and chlorobenzene over a site located in Shanghai, China. A sensitivity study revealed that the soil resistivity is a useful indicator of the presence of contaminants. Using the probabilistic method, a regional three-dimensional (3D) map of the probability that the soil is contaminated by the heavy metal ions or chlorobenzene is obtained based on the interpretation of resistivity data. Three selected sections of the resistivity-based 3D map are compared with those derived from the contaminant concentration data measured in the laboratory to demonstrate the effectiveness of the former. It is shown that the resistivity-based map is in accordance with concentration-based maps in a qualitative sense and provides useful information for the distribution of contaminants over the site. However, the resistivity-based probability shall always be judged with the results from the laboratory tests to draw a quantitative conclusion on the contamination status. Besides, it is also observed that the heavy metals may transfer over a narrower area than the chlorobenzene in the clay. The horizontal migration of contaminants is much more significant than that in the vertical direction, and it may be facilitated due to the presence of local geologic conditions.
Probabilistic identification of contaminated soils using resistivity piezocone penetration tests
The identification of contaminated soils has gained increasing interest over the decades in the geoenvironmental issues. In this study, a probabilistic method based on the geostatistics and the reliability-based analysis is performed on the resistivity piezocone penetration testing data to evaluate the spatial distribution of the contaminants including the heavy metal ions and chlorobenzene over a site located in Shanghai, China. A sensitivity study revealed that the soil resistivity is a useful indicator of the presence of contaminants. Using the probabilistic method, a regional three-dimensional (3D) map of the probability that the soil is contaminated by the heavy metal ions or chlorobenzene is obtained based on the interpretation of resistivity data. Three selected sections of the resistivity-based 3D map are compared with those derived from the contaminant concentration data measured in the laboratory to demonstrate the effectiveness of the former. It is shown that the resistivity-based map is in accordance with concentration-based maps in a qualitative sense and provides useful information for the distribution of contaminants over the site. However, the resistivity-based probability shall always be judged with the results from the laboratory tests to draw a quantitative conclusion on the contamination status. Besides, it is also observed that the heavy metals may transfer over a narrower area than the chlorobenzene in the clay. The horizontal migration of contaminants is much more significant than that in the vertical direction, and it may be facilitated due to the presence of local geologic conditions.
Probabilistic identification of contaminated soils using resistivity piezocone penetration tests
Acta Geotech.
Zou, Haifeng (author) / Liu, Songyu (author) / Cai, Guojun (author) / Puppala, Anand J. (author)
Acta Geotechnica ; 15 ; 761-779
2020-03-01
19 pages
Article (Journal)
Electronic Resource
English
Geostatistics , Probability of contamination , Reliability-based analysis , Resistivity piezocone penetration test Engineering , Geoengineering, Foundations, Hydraulics , Solid Mechanics , Geotechnical Engineering & Applied Earth Sciences , Soil Science & Conservation , Soft and Granular Matter, Complex Fluids and Microfluidics
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