Optimization of Triggered Fertigation for Sustainable Crop Production.

To achieve an optimal fertigation regime, it is essential to combine precise water and fertilizer application equipment and a decision support system. The decision support system usually comprises of a sensor network that collects quantitative information about water requirements of crops. In recent years there has been a plethora of work regarding various sensors and sensor networks for improving fertigation management and efficiency. However, information concerning the location of sensors is either, non-existent, empirical, experiential, or based on complicated spatio-temporal experiments, which are site and crop specific. Optimization of these parameters using field experiments would require numerous experiments, and a lot of time and work. Instead, in this study we propose to use the HYDRUS (2D/3D) model, a numerical code that simultaneously solves water flow and solute transport in homogeneous or heterogeneous soils, and water and nutrient uptake by plants, as a tool for investigating and optimizing different scenarios. Using several numerical examples we will demonstrate the application of this numerical model in decision making and its cost-effectiveness for optimizing fertigation regime. Furthermore this model can provide tools for estimating and preventing environmental damage by agricultural activities.

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