A 500-m Agricultural Drought Impact Dataset in China’s Main Grain Region: Toward Impact-Based Drought Monitoring
Year: 2026
Type: data-paper
Abstract: 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.
Source: Scientific Data
Institutions: Chinese Academy of Sciences, Institute of Geographic Sciences and Natural Resources Research, University of Chinese Academy of Sciences, Ministry of Emergency Management of the People's Republic of China, University of California, Irvine, United Nations University Institute for Water, Environment, and Health, King Abdullah University of Science and Technology, University of Nottingham Ningbo China
Language: English
Subfield: Global and Planetary Change
Field: Environmental Science
Domain: Physical Sciences
SDGs: Zero hunger, Climate action
Open Access status: gold
Estimated APC paid: $2,490
Award: G4585712238
OpenAlex ID: W7127634178