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Potential to predict depth‐specific soil–water content beneath an olive tree using electromagnetic conductivity imaging
Author(s) -
Martinez G.,
Huang J.,
Vanderlinden K.,
Giráldez J. V.,
Triantafilis J.
Publication year - 2018
Publication title -
soil use and management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.709
H-Index - 81
eISSN - 1475-2743
pISSN - 0266-0032
DOI - 10.1111/sum.12411
Subject(s) - water content , mean squared error , calibration , soil science , inversion (geology) , remote sensing , moisture , environmental science , root mean square , mathematics , geology , statistics , materials science , geotechnical engineering , composite material , electrical engineering , paleontology , engineering , structural basin
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 m 3 /m 3 , a mean error ( ME ) of 0.001 m 3 /m 3 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.