Identifying Potential Leakage Zones in an Irrigation Supply Channel by Mapping Soil Properties Using Electromagnetic Induction, Inversion Modelling and a Support Vector Machine

The clay alluvial plains of Namoi Valley have been intensively developed for irrigation. A condition of a license is water needs to be stored on the farm. However, the clay plain was developed from prior stream channels characterised by sandy clay loam textures that are permeable. Cheap methods of soil physical and chemical characterisations are required to map the supply channels used to move water on farms. Herein, we collect apparent electrical conductivity (ECa) from a DUALEM-421 along a 4-km section of a supply channel. We invert EC(a)to generate electromagnetic conductivity images (EMCI) using EM4 Soil software and evaluate two-dimensional models of estimates of true electrical conductivity (sigma-mS m(-1)) against physical (i.e., clay and sand-%) and chemical properties (i.e., electrical conductivity of saturated soil paste extract (ECe-dS m(-1)) and the cation exchange capacity (CEC, cmol(+) kg(-1)). Using a support vector machine (SVM), we predict these properties from the sigma and depth. Leave-one-site-out cross-validation shows strong 1:1 agreement (Lin's) between the sigma and clay (0.85), sand (0.81), ECe(0.86) and CEC (0.83). Our interpretation of predicted properties suggests the approach can identify leakage areas (i.e., prior stream channels). We suggest that, with this calibration, the approach can be used to predict soil physical and chemical properties beneath supply channels across the rest of the valley. Future research should also explore whether similar calibrations can be developed to enable characterisations in other cotton-growing areas of Australia.