Abstract

Although irrigation systems largely sustain global agricultural production, their efficiency is often alarmingly low. While irrigation water (blue water) is critical for the water-saving irrigation of rice with a high water demand, the process and efficiency of irrigation water utilization need clarification. In this study, we examined the three commonly used irrigation and drainage patterns (frequent shallow irrigation (FSI), wet and shallow irrigation (WSI), and rain-catching and controlled irrigation (RCI)) in rice fields. We developed a tracking method for irrigation water flow decomposition, which includes irrigation water evapotranspiration (IET), irrigation water drainage (IDR), irrigation water leakage (IPC), and irrigation water field residual (IRE). Using this method, we established an irrigation water efficiency evaluation index system and a comprehensive evaluation method. Our tracking method is relevant to describing the irrigation water performance under varying irrigation and drainage patterns. The results revealed that the average irrigation water input for the three irrigation and drainage patterns between 2015 and 2018 was roughly 312.5 mm, wherein IET accounted for 148 mm. However, more than 50% of the irrigation water outflow, comprising IDR, IPC, and IRE, exceeded the total amount of irrigation water input. The mean values of the gross irrigation efficiency (GIE), net irrigation efficiency (NIE), and effective consumption ratio (ECR) for all treatments in the three-year period were 0.63, 0.47, and 0.75, respectively. Additionally, the irrigation water use efficiency was significantly higher in dry years compared to wet years. The fuzzy composite rating values of the three irrigation and drainage models from 2015 to 2018 were RCI, WSI, and FSI, in descending order, under varying precipitation conditions. The RCI patterns maintained a high composite rating value (greater than 3.0) under different precipitation conditions. Previous efficiency calculations disregarded the blue–green water migration process and did not differentiate the blue–green water flow direction in agricultural fields, creating significant biases in the outcomes. This study’s method offers a new approach to evaluate the use of blue water resources in farmland.

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