Optimizing Irrigation Depth Using a Plant Growth Model and Weather Forecast

Numerical models of crop response to irrigation and weather forecasts with internet access should be fully utilized in modern irrigation management. In this respect, we developed a new numerical scheme to optimize irrigation depth that maximizes net income. Net income was calculated as a function of cumulative transpiration over irrigation interval which depends on irrigation depth. To evaluate this scheme, we carried out a field experiment for groundnut (Arachis hypogaea L.) grown in a sandy field of the Arid Land Research Center, Tottori University, Japan. Two treatments were established to compare the net income of the proposed scheme with that of an automated irrigation system. Results showed that although the proposed scheme gave a larger amount of seasonal irrigation water 28%, it achieved 2.18 times of net income owing to 51% higher yield compared to results of the automated irrigation system. This suggests that the proposed scheme would be more economical tool than automated irrigation systems to optimize irrigation depths.