Abstract: The information of the temporal and spatial distribution of irrigation events is of great significance for protecting the cultivated land quality and coping with climate change. Irrigation information can traditionally be captured using farmland water conservancy construction and field investigation. However, there is a great variation in the time and space of irrigation information from the different regions, due to the various water sources, planting structures, irrigation technology, water transmission, and measurement facilities. At the same time, remote sensing can be expected to timely and accurately monitor the ground surface all day. The previous research focused mainly on the crop growing season without considering the influence of different vegetation coverage on the irrigation remote sensing signals. Therefore, it is very necessary to detect the year-round events of farmland irrigation using remote sensing, particularly for different vegetation coverage. In this study, the farmland irrigation events were detected in the arid areas of northwest China using remote sensing. The research area was taken as Daman Super Station in Ganzhou District, Zhangye City, Gansu Province, China. The comparison was also performed on the conventional, near-infrared band reflectivity with MOD09GA optical remote sensing data, segmented PDI differential threshold model, microwave moisture products, and the combination of PDI differential threshold and microwave moisture products. An optimal scheme was achieved in the remote sensing detection suitable for all-year farmland irrigation events with different vegetation coverage. The performance was finally tested from the space-time dimension. The results show that there was a strong negative linear correlation between the PDI difference threshold and NDVI. Thus, a segmented PDI difference threshold model was constructed in 2016; The highest accuracy of irrigation events was achieved in the microwave moisture products combined with the PDI differential threshold. There was a close relationship between the soil surface water after irrigation and the response of vegetation to the soil water supply. The content of soil water reached saturation after irrigation. But the soil surface water continued to decrease and then returned to the pre-irrigation water content in about three days, due mainly to the evaporation. Furthermore, the microwave data was more sensitive to the surface soil moisture than the vegetation, indicating the dominant soil dielectrics. The high time resolution was realized to timely and effectively capture the occurrence of irrigation events. However, the electromagnetic wave energy was attenuated by crops with the increase in crop coverage. The water status of the soil surface failed to be monitored. Therefore, it was suitable for the case of no crops or low vegetation coverage. Moreover, the time resolution was low in the optical data. The content of soil surface water was captured in time, but it was also sensitive to the vegetation. Plant growth was subjected to water stress before irrigation. Once the soil water supply was sufficient, a significant difference was found in the vegetation water content and leaf structure, indicating the vegetation spectral in the near-infrared and red bands before irrigation. Optical data was used to indirectly monitor the irrigation events using these spectral. In particular, microwave water products were compensated for the irrigation monitoring the vigorous growth of crops or high coverage. The best performance was achieved in dry years, followed by normal years. The regional inversion showed that the distribution map of irrigation times made by microwave moisture products combined with the PDI differential threshold was consistent with the actual situation. The farmland with low irrigation capacity was distributed mainly on the edge of Zhangye Basin, which was far from the river, indicating the greater risk of climate change. Therefore, it was suitable to use microwave moisture products combined with PDI differential threshold in the detection and application of irrigation events in arid areas of northwest China. The findings can provide a theoretical basis for the efficient acquisition of actual irrigation information, cultivated land quality protection, and response to climate change.