|Ottman, M - UNIV OF AZ, TUCSON, AZ|
|Pinter, JR., Paul - RETIRED, USDA-ARS, PHX|
Submitted to: Transactions of the ASABE
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: January 15, 2007
Publication Date: December 20, 2007
Citation: Hunsaker, D.J., Fitzgerald, G.J., French, A.N., Clarke, T.R., Ottman, M.J., Pinter, Jr., P.J. 2007. 2007. Wheat Irrigation Management Using Multispectral Crop Coefficients. II. Effects of Irrigation Scheduling on Soil Water Depletion, Grain Yield, and Water Use Efficiency. Transactions of the ASABE. 50(6):2035-2050 Interpretive Summary: Irrigation scheduling methods are used to determine when to irrigate crops and how much water to apply. For proper scheduling, an irrigator needs to know the amount of water that is removed from the soil each day by crop evapotranspiration (ET). Yet, irrigation scheduling decisions are complicated because it is difficult to determine the actual amount of ET that occurs within an irrigated field, and the amount often differs from location to location. This research developed a remote sensing approach for determining actual ET that was used to schedule irrigations for wheat grown under both typical and nontypical wheat farming practices. Irrigation scheduling using the remote sensing approach provided more efficient use of irrigation water compared to irrigation scheduling by a widely used standard ET estimation method. The remote sensing approach offers potential irrigation water savings for wheat production, which will be of interest to wheat growers, irrigation consultants, agricultural engineers, and governmental agencies and commercial entities, who control or regulate water supplies.
Technical Abstract: Current irrigation scheduling is based on well-established crop coefficient-reference evapotranspiration methods. However, appropriate irrigation scheduling can be negated when crop evapotranspiration (ETc) is poor due to imprecise crop coefficients. The premise of this research is that real-time monitoring of spatially and temporally distributed basal crop coefficients (Kcb) via remote sensing provides the information needed for obtaining proper irrigation scheduling. In this study, two Kcb estimation approaches were used to schedule irrigations for wheat during two seasons in Arizona: 1) a remote sensing approach that inferred Kcb separately for each plot using frequent observations of the normalized difference vegetation index (NDVI treatment) and 2) a standard approach in which a locally developed time-based Kcb curve was applied uniformly for all plots (FAO treatment). The Kcb data were incorporated within the FAO-56 dual crop coefficient procedures to calculate daily ETc and predict daily soil water depletion percentage (SWDp) of the root zone. Irrigations to plots were applied when the predicted SWDp of the root zone reached 45%. Six, sub-treatment combinations (three plant densities: typical, sparse, and dense and two N managements: high and low) were imposed to create spatial and temporal variations in water use among the wheat plots. For the FAO treatment, in which all plots were irrigated alike, the mean SWDp measured just prior to irrigations varied considerably among the six sub-treatments (25 to 55% over both seasons) due to differences in ETc. The NDVI method provided separate predictions of SWDp for each plot, enabling customized irrigation schedules to accommodate sub-treatment differences in water use. Consequently, NDVI sub-treatments were irrigated at a more consistent SWDp than for FAO, where the mean SWDp measured at irrigations was typically 45%'5% for NDVI plots during both seasons. Tailored irrigation scheduling for NDVI also corresponded to a reduction in mean seasonal irrigation water application of 8 and 13% compared to the FAO treatment for the first and second seasons, respectively. Although NDVI irrigation scheduling did not increase mean grain yields over the FAO treatment, irrigation water use efficiency was significantly increased during both seasons. Incorporating this remote sensing approach within existing crop coefficient algorithms provides an opportunity to improve wheat irrigation scheduling strategies for attaining efficient use of irrigation water while maintaining grain yield potential.