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

Panagiota Antonia Petsetidi () and George Kargas
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Panagiota Antonia Petsetidi: Laboratory of Agricultural Hydraulics, Department of Natural Resources Management and Agricultural Engineering, Agricultural University of Athens, Iera Odos 75, 11855 Athens, Greece
George Kargas: Laboratory of Agricultural Hydraulics, Department of Natural Resources Management and Agricultural Engineering, Agricultural University of Athens, Iera Odos 75, 11855 Athens, Greece

Land, 2024, vol. 13, issue 9, 1-14

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

Keywords: WET; sensor; calibration; soil moisture (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2024
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