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Evaluation of five composite dielectric mixing models for understanding relationships between effective permittivity and unfrozen water content.
- Source :
-
Cold Regions Science & Technology . Oct2016, Vol. 130, p33-42. 10p. - Publication Year :
- 2016
-
Abstract
- Accurate estimation of unfrozen/liquid water content (θ l ) of soils with time domain reflectometry (TDR) is important for understanding freezing and thawing processes and hydrology in cold regions. Empirical equations and composite dielectric mixing models are the two most commonly used methods to estimate water content in unfrozen soils from TDR-measured soil effective permittivity (ε eff ). However, empirical equations derived from unfrozen soil data always overestimate θ l in frozen soils and few studies were found to examine the validity of composite dielectric mixing models for measuring θ l . Therefore, the objective of this study was to evaluate the sensitivities and applicability of composite dielectric mixing models for modeling the ε eff (θ l ) relationship. Five multi-phase, composite dielectric mixing models (i.e., power law model, de Loor model, Sihvola discrete model, Sihvola confocal model, and Sphere model) were evaluated with published dataset consisting of independently measured ε eff and θ l on the same samples. The results show that: (1) the power law model and de Loor models are independent of configurations of dielectric mixtures; (2) the Sihvola discrete model depends on the host medium and independent on the configurations of the other components; (3) different dielectric mixing models may end up with the similar ε eff (θ l ) relationships by parameter adjusting to represent the same problem; and (4) the de Loor model, and Sihvola discrete and confocal models are most appropriate for modeling the ε eff (θ l ) relationship of frozen soils based on the published dataset. This study will significantly contribute to the application of TDR method for liquid water measurement in frozen soils and facilitate the understanding of freezing/thawing processes. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 0165232X
- Volume :
- 130
- Database :
- Academic Search Index
- Journal :
- Cold Regions Science & Technology
- Publication Type :
- Academic Journal
- Accession number :
- 117583678
- Full Text :
- https://doi.org/10.1016/j.coldregions.2016.07.006