Potential to predict depth‐specific soil–water content beneath an olive tree using electromagnetic conductivity imaging

Abstract

AbstractEfficient monitoring of soil moisture is becoming increasingly important. To understand soil–plant–water dynamics, we evaluate the potential of using a multiple‐coil‐array electromagnetic induction instrument and inversion software to map soil moisture beneath an olive tree. On twelve different days, we collected apparent electrical conductivity (ECa) data using a DUALEM‐21S and the volumetric soil moisture (θ) using a bank of soil moisture sensors on opposite sides of the tree. Using EM4Soil, we inverted the ECa data on five of the days and established a site‐specific calibration between estimates of true electrical conductivity (σ) and θ. The strongest calibration relationship between σ and θ (R2 = 0.65) was obtained for a full‐solution, S2 algorithm and damping factor of 1.2. A leave one out cross‐validation (LOOCV) showed the calibration was robust, with a root mean square error (RMSE) of 0.046 m3/m3, a mean error (ME) of 0.001 m3/m3 and a Lin's concordance of 0.72. We subsequently evaluated the calibration relationship on the seven remaining days and over a drying period of 120 days. This approach provides information about the temporal evolution of θ by a LOOCV of validation with a RMSE of 0.037, ME of −0.003 and a Lin's concordance of 0.54. Improvement could be achieved by aligning the DUALEM‐21S in the same orientation as the sensors, with time‐lapse inversion also being advantageous.