Estimating pore water electrical conductivity of sandy soil from time domain reflectometry records using a time-varying dynamic linear model
PublisherMultidisciplinary Digital Publishing Institute (MDPI)
Rights accessOpen Access
Despite the importance of computing soil pore water electrical conductivity (sp) from soil bulk electrical conductivity (sb) in ecological and hydrological applications, a good method of doing so remains elusive. The Hilhorst concept offers a theoretical model describing a linear relationship between sb, and relative dielectric permittivity (eb) in moist soil. The reciprocal of pore water electrical conductivity (1/sp) appears as a slope of the Hilhorst model and the ordinary least squares (OLS) of this linear relationship yields a single estimate ( 1/spˆ ) of the regression parameter vector (sp) for the entire data. This study was carried out on a sandy soil under laboratory conditions. We used a time-varying dynamic linear model (DLM) and the Kalman filter (Kf) to estimate the evolution of sp over time. A time series of the relative dielectric permittivity (eb) and sb of the soil were measured using time domain reflectometry (TDR) at different depths in a soil column to transform the deterministic Hilhorst model into a stochastic model and evaluate the linear relationship between eb and sb in order to capture deterministic changes to (1/sp). Applying the Hilhorst model, strong positive autocorrelations between the residuals could be found. By using and modifying them to DLM, the observed and modeled data of eb obtain a much better match and the estimated evolution of sp converged to its true value. Moreover, the offset of this linear relation varies for each soil depth
CitationAljoumani, B.; Sanchez-Espigares, J.; Wessolek, G. Estimating pore water electrical conductivity of sandy soil from time domain reflectometry records using a time-varying dynamic linear model. "Sensors", 13 Desembre 2018, vol. 18, núm. 12, p. 4403-4414.