A method for spatial prediction of daily soil water status for precise irrigation scheduling

Available water holding capacity (AWC) and field capacity (FC) maps have been produced using regression models of high resolution apparent electrical conductivity (EC_a) data against AWC (adj. R² = 0.76) and FC (adj. R² = 0.77). A daily time step has been added to field capacity maps to spatially predict soil water status on any day using data obtained from a wireless soil moisture sensing network which transmitted hourly logged data from embedded time domain transmission (TDT) sensors in EC_a-defined management zones. In addition, regular time domain reflectometry (TDR) monitoring of 50 positions in the study area was used to assess spatial variability within each zone and overall temporal stability of soil moisture patterns. Spatial variability of soil moisture within each zone at any one time was significant (coefficient of variation [% CV] of volumetric soil moisture content (θ) = 3-16%), while temporal stability of this pattern was moderate to strong (bivariate correlation, R = 0.52-0.95), suggesting an intrinsic soil and topographic control. Therefore, predictive ability of this method for spatial characterisation of soil water status, at this site, was limited by the ability of the sensor network to account for the spatial variability of the soil moisture pattern within each zone. Significant variability of soil moisture within each EC_a-defined zone is thought to be due to the variable nature of the young alluvial soils at this site, as well as micro-topographic effects on water movement, such as low-lying ponding areas. In summary, this paper develops a method for predicting daily soil water status in EC_a-defined zones; digital information available for uploading to a software-controlled automated variable rate irrigation system with the aim of improved water use efficiency. Accuracy of prediction is determined by the extent to which spatial variability is predicted within as well as between EC_a-defined zones.