Site-specific estimation of spatiotemporal crop evapotranspiration through field-level sensing data

This study integrated field-level sensor data into the FAO-56 Penman-Monteith algorithm to provide a site-specific estimate of crop evapotranspiration. This was carried out at two contrasting sites for pea and bean (Manawatu) and barley (Hawke's Bay) crops managed within two irrigation management zones, at each site, under variable-rate irrigation systems in New Zealand. Daily crop evapotranspiration estimates were calculated using data from a weather station situated at the field site combined with in-field crop sensing data (spectral reflectance, canopy temperature, and canopy height). In addition, calibrated soil moisture data were used with a soil water balance model to compare estimations of daily crop evapotranspiration with those estimated using the crop sensing method. The results indicated that variable crop responses to different irrigation strategies and soil types provided a good opportunity to quantify different levels of spectral reflectance, canopy temperature, and consequently the estimation of crop water use. The statistical comparisons revealed that the modified FAO-56 Penman-Monteith using crop sensor data compared well with the more conventional soil water balance approach using soil moisture data (R-2 = 0.70, 0.83, 0.91 for barley, pea, and bean, respectively). Overall, the results from this study indicated that crop sensing approaches combined with the FAO-56 Penman-Monteith model have potential to provide a more easily determined site-specific field estimation of crop evapotranspiration than other methods, and it can take into consideration the spatiotemporal variability of crop growth in a field.