Li et al. (2026) Global maize yield-loss risk under atmospheric–soil moisture compound drought: Roles of phenology and cropping systems

Identification

• Journal: Agricultural Water Management
• Year: 2026
• Date: 2026-10-06
• Authors: Yangyang Li, Shuanggen Jin
• DOI: 10.1016/j.agwat.2026.110838

Research Groups

• School of Geomatics and Aerospace Information, Henan Polytechnic University
• School of Artificial Intelligence, Anhui University

Short Summary

This study develops a copula-based Climate-Land Drought Index (CLDI) to characterize water-deficit compound drought in global maize-growing regions. The CLDI integrates meteorological drought information from SPEI and soil-moisture drought information within an empirical-copula framework.

Objective

• Develop a globally consistent analytical framework that combines compound drought characterization, phenological-stage partitioning, and rainfed-irrigated system differentiation to assess stage-specific exposure and yield-loss responses in maize-growing regions.

Study Configuration

• Spatial Scale: Global maize-growing regions at 0.25° resolution.
• Temporal Scale: 1981–2024 for drought characterization and 1982–2015 for yield-response analysis.

Methodology and Data

• Models used: Empirical-copula framework to integrate SPEI and SSI within a common probabilistic space.
• Data sources: ERA5-Drought, ERA5-Land, Global CropYield5min dataset, FAO Global Agro-Ecological Zones (GAEZ v4) data portal, EM-DAT, and NOAA Center for Satellite Applications and Research (STAR).

Main Results

• The CLDI showed consistent associations with vegetation condition and maize yield anomalies.
• During 1981–2024, 37.1% of global maize-growing areas showed significant drying, accompanied by increasing frequency and persistence of severe-to-extreme drought.
• Yield-loss patterns differed across phenological stages: under severe-to-extreme drought, the reproductive stage (S2) was associated with the highest observed yield-loss probability (≈62.5%).

Contributions

• This study provides a globally consistent analytical framework that combines compound drought characterization, phenological-stage partitioning, and rainfed-irrigated system differentiation.
• The CLDI integrates meteorological drought information from SPEI and soil-moisture drought information within an empirical-copula framework.

Funding

• Not specified in the provided text.

Citation

@article{Li2026Global,
  author = {Li, Yangyang and Jin, Shuanggen},
  title = {Global maize yield-loss risk under atmospheric–soil moisture compound drought: Roles of phenology and cropping systems},
  journal = {Agricultural Water Management},
  year = {2026},
  doi = {10.1016/j.agwat.2026.110838},
  url = {https://doi.org/10.1016/j.agwat.2026.110838}
}