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Application of Multiphase Dielectric Mixing Models for Understanding the Effective Dielectric Permittivity of Frozen Soils
Author(s) -
He Hailong,
Dyck Miles
Publication year - 2013
Publication title -
vadose zone journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.036
H-Index - 81
ISSN - 1539-1663
DOI - 10.2136/vzj2012.0060
Subject(s) - permittivity , soil water , dielectric , reflectometry , water content , relative permittivity , soil science , materials science , dielectric permittivity , hysteresis , bound water , mineralogy , geotechnical engineering , environmental science , geology , time domain , chemistry , condensed matter physics , physics , computer science , optoelectronics , computer vision , organic chemistry , molecule
The time domain reflectometry (TDR)–measured effective permittivity in frozen soil conditions is affected by many complex factors including bound water effects on soil water permittivity, phase changes, soil microstructure and relative positions of soil constituents with respect to each other. The objective of this study was to improve understanding of some of the factors affecting the effective permittivity of frozen soils through the use of dielectric mixing models. Published datasets and frozen and unfrozen soil data measured on western Canadian soils were investigated with multiphase discrete and confocal ellipsoid models available in the literature. The results revealed that adjusting model parameters allowed the mixing models to describe the frozen soil permittivity equally well when bound water effects and temperature‐dependent water permittivity effects were included or not included. Measurement of freezing and thawing curves on western Canadian soils showed significant hysteresis and some mechanisms for this observed hysteresis and its influence on the interpretation of published datasets are discussed. When independent measurements of liquid water, ice and effective permittivity are available, it is possible to find one set of model parameters that reasonably predict effective permittivity for both frozen and unfrozen conditions. In frozen soils the predictive capability of the models is constrained to scenarios where the initial water content prior to freezing (i.e., the total water content) in the sampling volume is constant.

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