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

TL;DR

This paper introduces a high-resolution dataset tracking agricultural drought impacts in China's main grain region from 2006 to 2020.

Contribution

The study presents a novel 500 m-gridded agricultural drought-impacted area dataset for China’s main grain region.

Findings

The dataset accurately captures temporal and spatial variability of drought impacts across different crop seasons.

Validation confirms the dataset's reliability in representing drought-covered, drought-damaged, and crop failure areas.

The dataset provides a foundation for improving drought management and agricultural practices.

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.

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