STOCHASTIC-DOMINANCE ANALYSIS FOR MORE PROFITABLE AND LESS RISKY IRRIGATION OF CORN

Irrigation has long been used in arid regions to increase yields and reduce production risk. More recently, irrigation has gained popularity as a risk management tool in humid and subhumid regions. This study was conducted to determine stochastically efficient irrigation strategies and corresponding irrigation initiation thresholds. Stochastic Dominance analysis was applied to net returns to ascertain the stochastically efficient strategies and associated irrigation trigger levels for corn (Zea mays L.) in the Coastal Plain of Georgia. The CERES-Maize (V1.01) simulation model was used to estimate corn yields and associated quantities of applied irrigation water for the study. Three strategies with associated irrigation trigger levels were found to be stochastically efficient with respect to second-degree stochastic dominance. These were (i) irrigate within 24 h after more than one-half of the tensiometers at the 15- and 30-cm depths reflect a soil moisture content of 20% of capacity, (ii) irrigate within 24 h after a plant stress factor of 70 to 80% is reached, (iii) irrigate twice, once at tassel emergence and again 21 d later in the amount of 1.3 to 2.0 in. If water conservation is essential, the latter two strategies should be preferred. The results of this study verify the importance of irrigation scheduling for enhanced profitability and risk management. The analytical framework employed can be used to derive stochastically efficient irrigation schedules for any number of crops and environmental conditions.