Response of winter wheat to different drought levels based on Google Earth Engine in the Huang-Huai-Hai Region, China

Remote sensing technologies are frequently employed in monitoring and evaluating agricultural meteorological disasters because they can provide high throughput and cost-effective accesses to obtain a variety of real-time spatial data related to crop growth information. Accurately and timely estimating the drought dynamics using remote sensing is valuable for improving crop management level and promoting agricultural sustainable development. In this study, the responses of winter wheat during the critical growth stages to different drought levels from 2010 to 2020 in the Huang-Huai-Hai (HHH) region of China were evaluated based on Google Earth Engine. Four critical developmental stages of winter wheat were highlighted: greening-jointing, jointingheading, heading-milking maturity, and milking maturity-maturity stages. The temperature vegetation dryness index (TVDI) was constructed for evaluating the drought of winter wheat. Our results indicated that the winter wheat in the HHH region during 2010-2020 was clearly impacted by drought disasters, mainly mild to moderate droughts. In particular, the TVDI index during the critical development stages of winter wheat from 2010 to 2020 wavered in the scope of 0.48 and 0.61, and the soil moisture content at a depth of 10 cm tended to obviously reducing with a rate of - 0.1615/a. For critical growth stages, the winter wheat in the HHH Region was the most prone to threatened by drought during the stage of jointing-heading, following the stage of milking maturity-maturity. The high probability incidence of drought in winter wheat gradually shifted from the nutritional growth to the reproductive growth stages, which increased the risk of drought affecting yield. Furthermore, the notable spatial variations of drought in winter wheat in the HHH region were found. The winter wheat was evidently threatened by moderate and severe droughts in certain areas such as southern Hebei province, northern Jiangsu province, Anhui province, etc. Our results provide new insights into the studies on monitoring and evaluating agricultural meteorological disasters based on remote sensing technology.