Evaluation of a Multivariate Calibration Model for the WET Sensor That Incorporates Apparent Dielectric Permittivity and Bulk Soil Electrical Conductivity

The measurement of apparent dielectric permittivity (&epsilon:s) by low-frequency capacitance sensors and its conversion to the volumetric water content of soil (&theta:) through a factory calibration is a valuable tool in precision irrigation. Under certain soil conditions, however, &epsilon:s readings are substantially affected by the bulk soil electrical conductivity (ECb) variability, which is omitted in default calibration, leading to inaccurate &theta: estimations. This poses a challenge to the reliability of the capacitance sensors that require soil-specific calibrations, considering the ECb impact to ensure the accuracy in &theta: measurements. In this work, a multivariate calibration equation (multivariate) incorporating both &epsilon:s and ECb for the determination of &theta: by the capacitance WET sensor (Delta-T Devices Ltd., Cambridge, UK) is examined. The experiments were conducted in the laboratory using the WET sensor, which measured &theta:, &epsilon:s, and ECb simultaneously over a range of soil types with a predetermined actual volumetric water content value (&theta:m) ranging from &theta: = 0 to saturation, which were obtained by wetting the soils with four water solutions of different electrical conductivities (ECi). The multivariate model&rsquo:s performance was evaluated against the univariate CAL and the manufacturer&rsquo:s (Manuf) calibration methods with the Root Mean Square Error (RMSE). According to the results, the multivariate model provided the most accurate &theta: estimations, (RMSE &le: 0.022 m3m&minus:3) compared to CAL (RMSE &le: 0.027 m3m&minus:3) and Manuf (RMSE &le: 0.042 m3m&minus:3), across all the examined soils. This study validates the effects of ECb on &theta: for the WET and recommends the multivariate approach for improving the capacitance sensors&rsquo: accuracy in soil moisture measurements.