Abstract: Drought is a dynamic, ongoing process. Drought index, calculated over years, months, or specific stages of crop development as statistical periods, cannot accurately reflect the daily drought status of crops, and is somewhat insufficient in the research of daily dynamic monitoring of crop drought. Therefore, construction of a daily drought index considering the impact of the previous effect is an important support for the research and development of daily dynamic monitoring and early warning technology for crop drought occurrence, development, and recovery process. Winter wheat drought in the Huang-Huai-Hai Plain is targeted in this study, and daily meteorological data from 1981 to 2023, historical data on wheat drought, and data of winter wheat phenology are used to the construction of daily drought index (I_d), considering the water supply and demand of winter wheat at different stages. Coefficients of the previous effect of drought at 5 growth stages of winter wheat, i.e., before overwintering, during overwintering, greening-jointing, heading-filling, milk-maturity are determined, based on the distance between the drought and the non-drought samples. In addition, the effectiveness of I_d is validated using methods involving reserved independent samples, long time series, and spatial regional scales. Afterward, the drought process affecting winter wheat in 2022 is taken as an example to analyze the application of drought index I_d-based typical process tracking. Results show that the coefficients representing the previous effect of drought before winter wheat are 0.93, 0.88, 0.81, 0.92, and 0.95 for wheat before overwintering, during overwintering, greening-jointing, heading-filling and milk-maturity, respectively. The optimal previous effect coefficient value for the entire growth period of winter wheat is 0.90, indicating that the current drought is related to the drought conditions approximately 42 d prior. The accuracy of the reserved independent sample test for effectiveness of I_d is 88.40%; I_d of each stage in the years with drought and non-drought records shows a significant difference in typical station (Jiyang, Shandong) analysis, with stations (passing the test of 0.001 level) during typical years (2014-2015) with recorded drought disasters are located in areas characterized by low regional I_d values. The constructed drought index I_d for winter wheat demonstrates both temporal and spatial validity, providing valuable support for the development of daily monitoring, early warning, and real-time dynamic evaluation technologies for crop drought. The winter wheat drought index I_d can effectively represent the dynamic process of winter wheat drought in 2022, not only at targeted stations, but also on regional scales. The research findings can support the development of technologies for daily monitoring, early warning, and real-time dynamic evaluation of crop drought.