Abstract
Rational utilization of water resources is one of the major methods of water conservation. There are significant differences in the irrigation needs of different agricultural fields because of their spatial variability. Therefore, a decision support system for variable rate irrigation (DSS-VRI) by center pivot was developed. This system can process multi-spectral images taken by unmanned aerial vehicles (UAVs) and obtain the vegetation index (VI). The crop evapotranspiration model (ETc) and crop water stress index (CWSI) were obtained from their established relationships with the VIs. The inputs to the fuzzy inference system were constituted with ETc, CWSI and precipitation. To provide guidance for users, the duty-cycle control map was outputted using ambiguity resolution. The control command contained in the map adjusted the duty cycle of the solenoid valve, and then changed the irrigation amount. A water stress experiment was designed to verify the rationality of the DSS-VRI. The results showed that the more severe water stress is, the more irrigation is obtained, consistent with the expected results. Meanwhile, a user-friendly software interface was developed to implement the DSS-VRI function.
Highlights
China is a country with a water shortage, especially in its northwest regions
This study has proposed a decision support system for variable rate irrigation (DDS-Variable rate irrigation (VRI))
The inputted to the system were derived from unmanned aerial vehicles (UAVs) multispectral remote sensing images, and the duty-cycle data inputted to the system were derived from UAV multispectral remote sensing images, and the control map of the solenoid valve was obtained through the fuzzy inference system
Summary
China is a country with a water shortage, especially in its northwest regions. The shortage of water resources restricts agricultural development in many provinces, while the need for food has dramatically increased with the growth of the population. Agriculture is facing more serious challenges and requires effective ways for water-saving irrigation. Variable rate irrigation (VRI) is distinguished from traditional precision irrigation and provides such a solution. Previous VRI research has focused on quantitative decision-making models, partition management, decision support systems (DSS) and variable outputs [1]. There among, the quantitative decision-making model and partition management are key parts of VRI, variable output plays the role of executor, and DSS connected all parts of VRI
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