Optimal irrigation scheduling and crop production functions development using AquaCrop and TOMLAB

Water stress is one of the most influential factors contributing to crop yield loss. The importance of the irrigation constantly increases because of water scarcity and growing demand for agricultural production worldwide. Previously, an approach using empirical water production functions and analytic optimal control methodology has been developed for optimal irrigation scheduling. Such an approach based on numerical optimal control is an alternative to common irrigation scheduling based on agronomy practice. Nowadays, more complex dynamic crop simulation models, such as the FAO AquaCrop model, predict crop responses to different irrigation strategies and climates. The state variables of the AquaCrop model include crop characteristics, such as biomass, and soil water content in up to 12 soil layers. In this paper the numerical optimal control scheme for irrigation scheduling and crop water production function development is described and demonstrated using this model and the TOMLAB optimization library. Maize crop in Foggia, Italy, for season of the year 2000, is used as an illustrative case study.