Rice-irrigation automation using a fuzzy controller and weather forecast

Abstract

This paper presents a new irrigation controller based on fuzzy logic that uses weather forecast data and crop characteristics to evaluate the real-time need for irrigation of rice crops and to increase the efficiency of irrigation systems. Tests were performed with real data obtained from three different crop fields in Rio Grande do Sul State, Brazil, and on four meteorologically different days of the 2021/2022 harvest to demonstrate the ability to reduce power consumption for irrigation; the power consumption on days of heavy precipitation was above 80% under all simulated conditions. Depending on the size of the crop and the tested meteorological conditions, the minimum reductions in energy consumption were between 33–66% on dry days with no precipitation forecast. More than 15% reduction in the flow of the water catchment was also observed, even in the most adverse farming scenarios. This study reveals the necessity for technological advances in rice-crop irrigation systems to increase the efficiency of flood irrigation in large areas for reducing electricity consumption, increasing the profitability of rural producers, and ensuring the preservation and availability of water resources.