Partitioning evapotranspiration, yield prediction and economic returns of maize under various irrigation management strategies

Several maize field experiments, including deficit and full irrigation, were used to assess irrigation impacts on yields. The SIMDualKc water balance model was first calibrated and validated to obtain the basal crop coefficients (Kcb) and the depletion fractions for no stress (p) relative to all crop growth stages. The values 0.15, 1.15, 0.30 were obtained for, respectively, the Kcb ini, Kcb mid and Kcb end, as well as p = 0.50. The SIMDualKc model provided the partitioning of crop ET into transpiration and soil evaporation. The estimates of the actual transpiration of the maize crop under different irrigation schedules were used with the global and multiphasic Stewartʹs models (S1 and S2) to assess yields. A test was performed to compare the observed yield versus the models predicted yield. Good yield prediction was achieved with both S1 and S2 models; however, the S2 model performed better since it considers the distinct water stress effects at various crop growth stages. A RMSE of 1209 kg ha−1 was obtained for S2 yield estimates, which represents 6.8% of the observed average yield, while the RMSE for the S1 model represents 10%. Performance indicators relative to water productivity (WP) and the economic water productivity ratio (EWPR) were used to assess irrigation scheduling scenarios. Results show that the mild deficit scenario had the better WP. However, WP indicators are more sensitive to water use than to yield, which makes them less adequate for assessing the performance of irrigation water use at farm. Differently, when analysing scenarios under an economic perspective using full cropping costs with EWPR, deficit irrigation was ranked lower than full irrigation. This indicator shows to be more suitable to analyse economic viability of different irrigation strategies.