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.

摘要 本研究提出一种基于模糊逻辑（Fuzzy Logic）的新型灌溉控制器（Irrigation Controller），该控制器结合天气预报数据与作物特性，实时评估水稻作物的灌溉需求，以提升灌溉系统的运行效率。研究采用巴西南里奥格兰德州（Rio Grande do Sul）三块不同农田的实测数据，以及2021/2022收获季中4个气象条件各异的单日数据开展试验，验证了该控制器可降低灌溉能耗：在所有模拟工况下，强降水当日的灌溉能耗降幅均超80%；在无降水预报的干燥天气下，根据作物规模与测试气象条件的不同，最低能耗降幅可达33%至66%。此外，即便在最不利的农业生产场景中，集水流量也实现了15%以上的削减。本研究表明，水稻灌溉系统亟需技术升级，以提升大面积漫灌（Flood Irrigation）的运行效率，降低电力消耗，提升农业生产者的收益，并保障水资源的留存与可及性。