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

• Published in: Soil use and management Vol. 34; no. 2; pp. 236 - 248
• Main Authors: Martinez, G., Huang, J., Vanderlinden, K., Giráldez, J. V., Triantafilis, J.
• Format: Journal Article
• Language: English
• Published: Bedfordshire Wiley Subscription Services, Inc 01-06-2018
• Subjects: Calibration; Damping; Drying; DUALEM‐21S; Dynamics; Electrical conductivity; Electrical resistivity; Electromagnetic induction; Environmental monitoring; Fruit trees; Imaging techniques; Mathematical models; Moisture content; Orientation; quasi‐2D inversion; Root-mean-square errors; Sensors; Soil; Soil dynamics; Soil moisture; Soil water; volumetric moisture content; Water content; Water depth
• ISSN: 0266-0032; 1475-2743
• DOI: 10.1111/sum.12411

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 (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.