| Abstract: | Efficient 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 (EC a) 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 EM 4Soil, we inverted the EC a 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 (R 2 = 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. |
