Development of a Fuzzy Variable Rate Irrigation Control System Based on Remote Sensing Data to Fully Automate Center Pivots

Growing agricultural demands for the global population are unlocking the path to developing innovative solutions for efficient water management. Herein, an intelligent variable rate irrigation system (fuzzy-VRI) is proposed for decision-making to achieve optimized irrigation in various delimited zones. The proposed system automatically creates irrigation maps for a center pivot irrigation system for a variable rate application of water. Primary inputs are satellite imagery on remotely sensed soil moisture (SSM), soil-adjusted vegetation index (SAVI), canopy temperature (CT), and nitrogen content (NI). The system relates these inputs to set reference values for the rotation speed controllers and individual openings of each central pivot sprinkler valve. The results showed that the system can detect and characterize the spatial variability of the crop and further, the fuzzy logic solved the uncertainties of an irrigation system and defined a control model for high-precision irrigation. The proposed approach is validated through the comparison between the recommended irrigation and actual irrigation at two field sites, and the results showed that the developed approach gives an accurate estimation of irrigation with a reduction in the volume of irrigated water of up to 27% in some cases. Future research should implement the fuzzy-VRI real-time during field trials in order to quantify its effect on irrigation use, yield, and water use efficiency. Note to Practitioners—This work is motivated by the objective of managing irrigation more efficiently. It will be a site-specific irrigation management tool and we proposed a theoretical framework that aims an artificial intelligence approach to automatically create optimal control maps for a center pivot irrigation system. At the heart of this system will be the fuzzy logic, which will define the reference values for the rotation speed controllers and the individual opening of each center pivot sprinkler valve. Currently, there is a lack of these types of systems which ends up generating an increase in demand for more intelligent, automated, and accurate systems. The proposed system will be based on decision-making - whether to apply more or less water - and will use remote sensing data, therefore, the innovative irrigation system will efficiently describe the spatial variability of the crop. The results indicate that edaphoclimatic variables, when well combined with fuzzy logic, can resolve uncertainties and nonlinearities of an irrigation system and define a control model for high precision irrigation. However, it will not always be possible to reduce water consumption, but this technology has many uses to increase farm profitability.