MAPPING SOIL-SALINITY USING CALIBRATED ELECTROMAGNETIC MEASUREMENTS

A statistical modeling approach is presented that predicts spatial soil salinity patterns from aboveground electromagnetic induction (EM) readings. In this approach, EM readings are obtained from a field sampled on a uniform (centric systematic) grid. A small number of these sample sites are chosen for soil sampling, based on the observed EM field pattern. The salinity levels for these soil samples are determined and then the remaining nonsampled salinity values are predicted from the corresponding EM readings through a multiple linear regression equation. Experimental results suggest that this approach will work well in fields having low to moderate levels of soil textural variability. For example, 95% of the spatial variability in soil salinity within typical 16.2-ha (40-acre) cotton (Gossypium hirsutum L.) fields could be accounted for with only 36 soil samples, as opposed to the 200 to 300 soil samples typically required if no EM readings were available. This approach makes EM readings a more practical and cost-effective tool by substantially reducing the number of soil samples needed for accurate mapping of spatial salinity patterns at the field scale.