Cotton Irrigation Scheduling Using Soil Water Depletion Estimates of Small-Zones in Large Fields

Precision irrigation scheduling optimizes water application to small zones within a large field. For precision irrigation, accurate information is required to monitor the spatial and temporal variability of crop evapotranspiration (ETc) and the soil water supply.  However, for surface irrigation, precision irrigation scheduling is seldom considered. Our objective was to evaluate the use of spatio-temporal monitoring of soil water depletion (SWD) within surface-irrigated fields for cotton irrigation scheduling.  Field studies were conducted for two years at the Maricopa Agricultural Center (MAC), in Arizona, on a 5-ha site that included 16 large cotton borders. The borders were randomized within four blocks having four different irrigation scheduling treatments. One treatment (MAC) followed the traditional cotton scheduling approach used by MAC farm. Irrigation schedules for other treatments were based on SWD estimated for 160, 4 by 8 m zones per treatment.  The three treatments differed in crop coefficients for calculating ETc. Remote sensing of vegetation index (VI) was used for two treatments (VI_A and VI_B) to estimate crop coefficients, whereas the third treatment (FAO_A) used a single crop coefficient for all zones. Irrigations for VI_A and FAO_A were given when average SWD from all zones reached 45%.  For VI_B, irrigations were given when 5% of the zones reached 65% SWD.  Results showed that the agreement between estimated and measured ETc was superior for the VI_A and VI_B compared to that using the single crop coefficient for FAO_A.  In the first year, lint yields were significantly higher for VI_B and MAC, though total irrigation water applied to MAC was 7% higher than for VI_B.  In the second year, treatment lint yields were not significantly different.  The capability of spatial inputs used for irrigation scheduling may be more effective when spatial extremes are considered rather than using spatial averages to determine irrigation scheduling.