| Popis: |
Farms in Western Australia (WA) are highly variable in soil texture and water retention capacity; therefore, spatial information of soil moisture status in the field is important for crop management. In practice, farmers often rely on point sensors to determine soil moisture in their fields for crop planning. The limitation of point measurements to account for spatial variability highlights the need to develop methods to assess soil moisture across variable broadacre fields. This information could be used for more effective site-specific crop management practices. In this study, we used a mobile nonintrusive electromagnetic induction (EMI) sensor to map soil apparent electrical conductivity (ECa) and to predict soil moisture levels across the field at three depths (0 – 0.5, 0.5 – 0.8 and 0.8 – 1.6m). The predicted soil moisture was compared with the point measurements of soil moisture sensors and soil samples. The inverted electrical conductivity (EC) from EMI surveys was converted into soil moisture using calibrations between electrical resistivity tomography (ERT) to volumetric moisture, which were developed for the different soil textural classes of the field, with R2 of 0.97 to 0.99. The soil moisture variability of the field was also compared with the spatial distribution of 2019 barley yield production. No significant difference was found between the EMI estimated soil moisture values and the point moisture measurements, as well as moisture extracted from soil samples for 0 – 0.5m and 0.5 – 0.8 m depths with Pearson R values of 0.62 and 0.73 respectively. Barley yield was not correlated with mapped soil moisture or soil texture, which may be due to relatively high initial moisture levels following two years of fallow rotation. This study successfully demonstrated spatial soil moisture estimation using EMI sensor in a field with horizontally and vertically variable soil texture. |
