Three-dimensional imaging of subsurface structural patterns using quantitative large-scale multi-configuration electromagnetic induction data

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Title:Main Title: Three-dimensional imaging of subsurface structural patterns using quantitative large-scale multi-configuration electromagnetic induction data
Description:Abstract: Electromagnetic induction (EMI) systems measure the soil apparent electrical conductivity (ECa), which is related to the soil water content, texture and salinity changes. Large-scale EMI measurements show relevant areal ECa patterns, but only few researchers have attempted to resolve vertical changes in electrical conductivity that in principle can be obtained using multi-configuration EMI devices. In this work, we show that EMI measurements can be used to determine the lateral and vertical distribution of the electrical conductivity at the field scale and beyond. The processed ECa data for six configurations, measured at the Selhausen test site, are calibrated using inverted electrical resistivity tomography (ERT) data from a short transect with a high ECa range, and re-gridded using a nearest neighbor interpolation. The quantitative ECa data at each grid point are inverted by a novel three-layer inversion that uses the shuffled complex evolution (SCE) optimization and a Maxwell-based electromagnetic forward model. The obtained 1D-results are stitched together to form a quasi-3D subsurface electrical conductivity model that shows smoothly varying electrical conductivities and layer thicknesses, indicating the stability of the inversion results. The obtained electrical conductivity distributions are validated with low resolution lateral grain size distribution maps and two formerly measured 120 m long ERT transects that confirm the obtained lateral and vertical large-scale electrical conductivity patterns. Probably due to dynamic changes in soil moisture, small differences in the quantitative electrical conductivity values and layer thickness are observed, that, however, indicate that EMI-inversions can be used to infer hydrologically active layers.
Responsible Party
Creator:Christian von Hebel (Author)
Publisher:CRC/TR32 Database (TR32DB)
Publication Year:2016
Topic
TR32 Topic:Soil
Related Subproject:B6
Subjects:Keywords: Soil, PhD Report
File Details
Filename:CvH_EMI_report2-paperManuscript.docx
Data Type:Text - Text
File Size:121 KB
Date:Valid: 13.08.2013
Mime Type:application/vnd.openxmlformats-officedocument.wordprocessingml.document
Language:English
Status:Completed
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Download Permission:Only Project Members
General Access and Use Conditions:According to the TR32DB data policy agreement.
Access Limitations:According to the TR32DB data policy agreement.
Licence:[TR32DB] Data policy agreement
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Specific Information - Report
Report Date:9th of October, 2013
Report Type:PhD Report
Report City:Juelich
Report Institution:IBG-3
Metadata Details
Metadata Creator:Christian von Hebel
Metadata Created:03.05.2016
Metadata Last Updated:03.05.2016
Subproject:B6
Funding Phase:2
Metadata Language:English
Metadata Version:V50
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