1887

Abstract

Dielectric spectra have been widely explored to obtain information about material structural characteristics and physical constituents. As a mixture of three phases (cohesionless soil) or four phases (cohesive soil with significant amount of bound water), soil dielectric behavior is complicated by the phase interactions. Understanding the soil dielectric behavior is the prerequisite for application of technologies such as active remote sensing, ground penetration radar, Time Domain Spectroscopy, and other electromagnetic wave technologies for soils. The soil dielectric spectrum can be measured in the frequency domain, using a Network Analyzer or in the time domain by model-based inversion of recorded electromagnetic time signal. The model-based inversion is advantageous in that it is fast and the spectrum is less influenced by the presence of signal noise at individual frequencies. This paper evaluates the performance of several commonly used models for soil dielectric spectrum, including Debye’s model, Cole-Cole’s model, a power-law type volumetric mixing model, and a simplified model based on the concept of apparent dielectric constant. The model parameters were obtained from inversion analysis of TDR (Time Domain Reflectometry) measurements on soils. The performances of individual models are compared using statistical analysis of residuals. The analyses indicate that there is no significant difference between the capability of Debye’s model and Cole-Cole’s model for describing soil dielectric behavior, which possibly indicates that there are no pronounced distributive relaxation mechanisms inside the measured soil mixtures. While the volumetric mixing model better describes the trend of actual soil dielectric spectrum, it also causes increased non-uniqueness in the inversion process. The simplified model, although it could not fully characterize the soil dielectric spectrum, provides robust indication of soil dielectric behaviors within the TDR measurement range. The relative merits and shortcomings of each individual model are discussed in this paper.

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/content/papers/10.3997/2214-4609-pdb.183.215-225
2005-04-03
2024-03-28
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http://instance.metastore.ingenta.com/content/papers/10.3997/2214-4609-pdb.183.215-225
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