Optimal model-based deficit irrigation scheduling using AquaCrop: A simulation study with cotton, potato and tomato

• Optimal irrigation schedule is obtained by nonlinear constrained optimization.
• Initial guesses are obtained by sub-optimal optimization.
• The methodology is suitable for any crop modeled with AquaCrop.
• Cotton, potato and tomato are used as case studies.

Water shortage is the main limiting factor for agricultural productivity in many countries and improving water use efficiency in agriculture has been the focus of numerous studies. The usual approach to limit water consumption in agriculture is to apply water quotas and in such a situation farmers should use an irrigation schedule that maximizes the yield and abides to the quota constraints. In contrast to the widespread use of irrigation scheduling based on agronomy practices, irrigation scheduling may be considered as a constrained optimization problem. When drip irrigation is used, the decision variables are the irrigation amounts for each day of the season. The objective function is the expected yield calculated with the use of a model. In the present work we solved this optimization problem for three crops modeled by the model AquaCrop. This optimization problem is non-trivial due to the non-smooth behavior of the objective function and the fact that it involves multiple integer variables. We developed an optimization scheme for generating sub-optimal irrigation schedules that take implicitly into account the response of the crop to water stress, and used these as initial guesses for a full optimization of daily irrigation. Performing this optimization with various values of water quotas produced the function that expresses the relationship between water quota and yield.