Time domain reflectometry can be applied to measure soil bulk density. Monitoring of bulk density over large areas for geo-statistical analysis requires a fast and effective method allowing for acquisition of many data points. Methods are available in the literature to obtain density from TDR. However, algorithms for simultaneous measurements of density and soil water content are not available. Moreover, the methodologies presented in the literature requires tests and evaluation. In this study a new algorithm implemented into a software was developed and the method tested over samples having different textural properties. It is shown that the method provided a measurement of density with an accuracy between 1 and 3 %. The new algorithm implements an automated methodology combined with a non-linear least square optimization, allowing for analysis of many waveforms at a time. Several equations to derive soil water content from electric permittivity were tested, showing that dielectric mixing models provides more accurate results. Moreover, the optimization of parameters allows for analysis and application to multiple materials. The method was confirmed robust and suitable for field-monitoring applications.
Bittelli, M., Tomei, F., Anbazhagan, P., Pallapati, R.R., Mahajan, P., Meisina, C., et al. (2021). Measurement of soil bulk density and water content with time domain reflectometry: Algorithm implementation and method analysis. JOURNAL OF HYDROLOGY, 598(July 2021), 1-11 [10.1016/j.jhydrol.2021.126389].
Measurement of soil bulk density and water content with time domain reflectometry: Algorithm implementation and method analysis
Bittelli M.
;
2021
Abstract
Time domain reflectometry can be applied to measure soil bulk density. Monitoring of bulk density over large areas for geo-statistical analysis requires a fast and effective method allowing for acquisition of many data points. Methods are available in the literature to obtain density from TDR. However, algorithms for simultaneous measurements of density and soil water content are not available. Moreover, the methodologies presented in the literature requires tests and evaluation. In this study a new algorithm implemented into a software was developed and the method tested over samples having different textural properties. It is shown that the method provided a measurement of density with an accuracy between 1 and 3 %. The new algorithm implements an automated methodology combined with a non-linear least square optimization, allowing for analysis of many waveforms at a time. Several equations to derive soil water content from electric permittivity were tested, showing that dielectric mixing models provides more accurate results. Moreover, the optimization of parameters allows for analysis and application to multiple materials. The method was confirmed robust and suitable for field-monitoring applications.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.