A dielectric model of thawed and frozen Arctic soils considering frequency, temperature, texture and dry density. Issue 10 (18th May 2020)

• Record Type: Journal Article
• Authors: Mironov, V. L.; Karavayskiy, A. Yu.; Lukin, Yu. I.; Molostov, I. P.
• Is Part Of: International journal of remote sensing. Volume 41:Issue 10(2020)
• Page Start: 3845
• Page End: 3865
• Publication Date: 2020-05-18
• Subjects: Remote sensing -- Periodicals; Télédétection -- Périodiques; 621.3678
• DOI: 10.1080/01431161.2019.1708506
• Languages: English
• ISSNs: 0143-1161

Abstract

ABSTRACT: A dielectric model was developed for thawed and frozen mineral soils, based on the refractive mixing dielectric formula and the dielectric measurement data for three soils collected in the Arctic tundra of the Yamal Peninsula. The refractive mixing dielectric model was used in conjunction with the Debye multi relaxation equations as a theoretical model to fit the measured complex relative permittivity spectra as a function of soil moisture and temperature. As a result, the dielectric spectroscopic parameters for the various components of water in the soil, such as the low- and high-frequency limits of the complex relative permittivity, the times of the corresponding relaxations, and the specific conductivity, were simultaneously determined for soils with different clay contents for all measured temperatures. As the theoretical temperature dependences of these parameters, the Clausius–Mossotti, Eyring, and linear equations for the conductivity were used. By using approximations of the measured data with these formulas, the parameters of the temperature-dependent model were derived, such as the coefficient of volume expansion, energy and entropy of activation, and coefficient of thermal conductivity. A set of the parameters discussed above in conjunction with the refractive mixing formula is a temperature- and mineralogically dependent multi-relaxation spectroscopic dielectric model, which enables estimation of the permittivity of moist soils as a function of dry soil density, moisture, frequency, temperature, and texture. The statistical error of the proposed dielectric model was estimated in terms of the normalized root-mean-square error (nRMSE), which was equal to 5% and 25% for the dielectric constant and dielectric loss factor, respectively.