Laboratory Calibration and Field Validation of Soil Water Content and Salinity Measurements Using the 5TE Sensor

Abstract

Capacitance sensors are widely used in agriculture for irrigation and soil management purposes. However, their use under saline conditions is a major challenge, especially for sensors operating with low frequency. Their dielectric readings are often biased by high soil electrical conductivity. New calculation approaches for soil water content (θ) and pore water electrical conductivity (ECp), in which apparent soil electrical conductivity (ECa) is included, have been suggested in recent research. However, these methods have neither been tested with low-cost capacitance probes such as the 5TE (70 MHz, Decagon Devices, Pullman, WA, USA) nor for field conditions. Thus, it is important to determine the performance of these approaches and to test the application range using the 5TE sensor for irrigated soils. For this purpose, sandy soil was collected from the Jemna oasis in southern Tunisia and four 5TE sensors were installed in the field at four soil depths. Measurements of apparent dielectric permittivity (Ka), ECa, and soil temperature were taken under different electrical conductivity of soil moisture solutions. Results show that, under field conditions, 5TE accuracy for θ estimation increased when considering the ECa effect. Field calibrated models gave better θ estimation (root mean square error (RMSE) = 0.03 m3 m−3) as compared to laboratory experiments (RMSE = 0.06 m3 m−3). For ECp prediction, two corrections of the Hilhorst model were investigated. The first approach, which considers the ECa effect on K’ reading, failed to improve the Hilhorst model for ECp > 3 dS m−1 for both laboratory and field conditions. However, the second approach, which considers the effect of ECa on the soil parameter K0, increased the performance of the Hilhorst model and gave accurate measurements of ECp using the 5TE sensor for irrigated soil.

Field Comparison of Electrical Resistance, Electromagnetic Induction, and Frequency Domain Reflectometry for Soil Salinity Appraisal

“…Certainly, the inclusion of other soil properties for the estimation of the σ e and thus salinity appraisal improved the prediction, giving rise to models with R 2 and RMSE values of 0.44 and 1.8 dS m −1 , 0.34 and 2.1 dS m −1 , and 0.59 and 1.7 dS m −1 for, respectively, the SCT-10, the EM38, and the WET-2. Apparently, these model performance coefficients do not compare well with the ones obtained in other works, e.g., Zemni et al [34] achieved RMSE values below 1 dS m −1 for a CCC probe, and Samson et al [22] R 2 up to 0.98 for CCC and TDR probes. However, compared to theirs and other researchers', the testing conditions of the study area in this work were very challenging because of its large extension and thus diversity of soils.…”

“…Empirical or semi-empirical calibrations have been almost always used to estimate σ e from σ b , and since the σ b values obtained with the different available sensors are also different, not only site-specific, but also sensor-proprietary calibrations have been developed [20][21][22]. The calibrations have been developed mostly under laboratory conditions using sandy soils [22,33,34]. Besides, some comparisons between different techniques for σ b measurement have been carried out, e.g., ER vs. TDR [22], TDR vs. FDR [35], ER vs. FDR [21], and EMI vs. TDR [18,36].…”

Smart Sensing with Edge Computing in Precision Agriculture for Soil Assessment and Heavy Metal Monitoring: A Review

“…In order to measure soil water content and salinity, Zemni et al [100] used 5TE sensors at different soil depths to assess dielectric permittivity (Ka) and electrical conductivity (ECa). It is to be noted that 5TE sensors are based on frequency domain reflectometry (FDR); therefore, they use a fixed frequency wave of broadband signal which makes the device cheaper and more compact.…”