HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS		QUICK SEARCH:   [advanced] Author: Keyword(s): Year:  Vol:  Page:

This Article Figures Only Full Text Full Text (PDF) Alert me when this article is cited Alert me if a correction is posted Services Similar articles in this journal Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via Google Scholar Google Scholar Articles by Schwartz, R.C. Articles by Bell, J.M. Search for Related Content PubMed Articles by Schwartz, R.C. Articles by Bell, J.M. Agricola Articles by Schwartz, R.C. Articles by Bell, J.M. Related Collections Soil Methods/Instrumentation Water Content Time Domain Reflectometry, TDR

SOIL PHYSICS

Complex Permittivity Model for Time Domain Reflectometry Soil Water Content Sensing: II. Calibration

USDA-ARS, Conservation and Production Research Lab., Bushland, TX 79012

^* Corresponding author (robert.schwartz{at}ars.usda.gov).

Despite numerous applications of time domain reflectometry (TDR), serious difficulties in estimating accurate soil water contents under field conditions remain, especially in fine-textured soils. A complex dielectric mixing model was calibrated for fine-textured soils (24–45% clay) and its accuracy was evaluated and compared with empirical calibrations. The Ap and Bt horizons of two soils were packed into columns and adjusted to volumetric water contents () ranging from air dry to near saturation. Travel time and bulk electrical conductivity (₀) were measured using TDR at temperatures (T) of 8, 22, and 40°C and using three coaxial cables to obtain a range of input spectrum bandwidths (_S). Apparent permittivities (K_a) were predicted using the complex permittivity model with measured , T, ₀, _S, and soil bulk density, and fitted to measured K_a by optimizing specific surface area (A_s), the power-law exponent (a), and an empirical polarization loss factor. Measured K_a was best approximated using the power-law dielectric mixing model with a semiempirical effective frequency estimate and a = 0.68. Predicted A_s increased with increasing clay content, cation exchange capacity, and measured specific surface areas. The two-parameter power-law calibration removed temperature bias in estimates and reduced the RMSE in estimates by an average of 0.006 m³ m^–3 compared with an empirical calibration. Empirical models predicted field with oscillations of up to 0.022 m³ m^–3 in phase with soil temperatures resulting from permittivity temperature dependencies. In contrast, the calibrated dielectric mixing model removed or dampened in-phase fluctuations to <0.004 m³ m^–3, which permitted the detection of more subtle changes (<0.02 m³ m^–3) in .

Abbreviations: BET, Brunauer, Emmett, and Teller • RSD, residual standard deviation • TDR, time domain reflectometry