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Soil water (θ) dynamics are important parameters to monitor in any field-based drought research. Although apparent electrical conductivity (ECa) measured by electromagnetic (EM) induction has been used to estimate θ, little research has shown its successful application at the plot-scale for evaluating crop water use. An EM38 conductivity meter was used to collect time-lapse ECa data at the plot scale across a field cropped with 36 different chickpea genotypes. An empirical multiple linear regression model was established to predict θ measured by neutron probes and depth-specific electrical conductivity (σ) generated by a 1-D EM inversion algorithm. Soil water dynamics and movement were successfully mapped with a coefficient of determination (R2) of 0.87 and root-mean-square-error of 0.037 m3 m−3. The rate of soil drying varied with depth and was influenced by chickpea growth stages and genotypes. The results were also used to evaluate the differences in soil water use and rooting depths within- and across-plant species and during the growth stages. Coupled with physiology measurements, the approach can also be used to identify mechanisms of drought tolerance in the field and screening for effective water use in crop breeding programs.

Soil Water Extraction Monitored Per Plot Across a Field Experiment Using Repeated Electromagnetic Induction Surveys