A 500-m Agricultural Drought Impact Dataset in China’s Main Grain Region: Toward Impact-Based Drought Monitoring

A high-resolution, quantitative dataset of agricultural drought impacts is essential for advancing impact-based drought monitoring and prediction. Yet, such data remain the critical missing piece, representing the major obstacle to developing robust, impact-driven drought assessments. Here, we generated a 500 m-gridded agricultural drought-impacted area dataset in the China’s main grain region (ADIA-CMGR) during 2006–2020. We employ a leaf area index (LAI)-based relative threshold method to extract the areas with three degrees of drought impacts for summer-harvest crops, autumn-harvest crops, and early rice, respectively. The dataset constitutes various information, including drought-covered area, drought-damaged area, and crop failure area. Validation with the text-based qualitative records of agricultural drought-impacted areas shows that ADIA-CMGR offers accurate temporal variability and reasonable spatial distribution. The developed dataset satisfactorily revealed the spatial and inter-annual dynamics of agricultural drought-impacted areas across various crop-growing seasons, providing a solid foundation for managing drought impacts and improving agricultural practices.