Open AccessComparison of Petrophysical Relationships for Soil Moisture Estimation using GPR Ground Waves
Author(s) -
Steelman Colby M.,
Endres Anthony L.
Publication year - 2011
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/vzj2010.0040
Subject(s) - water content , mean squared error , soil science , petrophysics , empirical modelling , ground penetrating radar , soil water , mathematics , permittivity , coefficient of determination , statistics , environmental science , dielectric , porosity , geology , radar , materials science , geotechnical engineering , telecommunications , optoelectronics , computer science , programming language
Soil water content measurement using ground‐penetrating radar (GPR) requires an appropriate petrophysical relationship between the dielectric permittivity and volumetric water content of the soil. The suitability of different relationships for GPR soil water content estimation has not been thoroughly investigated under natural field conditions for a complete range of seasonal soil conditions. In this study, we examined the ability of various empirical relationships, volumetric mixing formulae, and effective medium approximations to predict near‐surface volumetric soil water content using high‐frequency direct ground wave (DGW) velocity measurements for three soil textures. The estimated water contents were compared with values obtained from gravimetric sampling. The accuracy of soil water content predictions obtained from the various relationships ranged considerably. The best predictions for the overall data set in terms of RMSE were obtained with a differential effective medium approximation based on a coated sphere model (RMSE = 0.045 m 3 m −3 ); however, an empirical relationship (RMSE = 0.052 m 3 m −3 ) and a volumetric mixing formula (RMSE = 0.048 m 3 m −3 ) also performed well. These best‐fitting relationships do exhibit some degree of textural bias that should be considered in the choice of petrophysical relationship for a given data set. Further improvements in water content estimates were obtained using our best‐fit third‐order polynomial relationship (RMSE = 0.041 m 3 m −3 ) and our three‐phase volumetric mixing formula with geometric parameter α = 0.36 (RMSE = 0.042 m 3 m −3 ); these optimized relationships were developed using the DGW permittivity and soil water content data collected in this study.