Zhang et al. (2026) Identification of phenology-aligned sensitive windows to extreme-rainfall events for maize in north China Plain and actionable irrigation–drainage triggers

Identification

• Journal: Agricultural Water Management
• Year: 2026
• Date: 2026-08-27
• Authors: Lushuang Zhang, Changfeng Jing, Ziyi Zhou, Hong Wan
• DOI: 10.1016/j.agwat.2026.110722

Research Groups

• School of Artificial Intelligence, China University of Geosciences Beijing
• College of Information Science and Engineering, Shandong Agricultural University

Short Summary

This study identifies phenology-aligned sensitive windows to extreme-rainfall events for maize in the North China Plain and proposes actionable irrigation–drainage triggers. The Exposure Mismatch Index (EMI) is defined as the directional difference in cumulative threshold-exceeding precipitation between phenology-aligned and static calendar windows.

Objective

• Identify phenology-aligned exposure windows that accurately capture extreme rainfall during crop-sensitive stages.
• Quantify stage-relevant exposure under interannual phenological variation.
• Characterize how exposure–yield associations vary across heterogeneous irrigation contexts.

Study Configuration

• Spatial Scale: County-level data from the North China Plain (NCP) in China.
• Temporal Scale: 2001 to 2015.

Methodology and Data

• Models used: Generalized propensity score (GPS) weighting with generalized additive models (GAMs).
• Data sources:
  • Gridded yield, phenology, precipitation, soil, topographic, climatic, and irrigation datasets.
  • MODIS enhanced vegetation index (EVI) for crop phenology reconstruction.
  • Climate Hazards Group InfraRed Precipitation with Station data for daily precipitation.

Main Results

• The Exposure Mismatch Index (EMI) quantifies the difference in cumulative extreme precipitation exposure captured by a phenology-aligned window and its corresponding static calendar window.
• Static windows produce substantial W2 exposure misclassification throughout the examined range, with total misclassification rates ranging from 17.3% to 19.9%.
• The EMI–yield association is nonlinear for W2 in the <0.90 irrigation-coverage stratum, whereas comparable support is limited in the ≥0.90 irrigation-coverage stratum.

Contributions

• This study provides a regional screening indicator of exposure-window mismatch.
• A positive mismatch prompts a review of drainage readiness, whereas a negative mismatch should prompt an assessment of soil-water availability.

Funding

• Not specified in the provided text.

Citation

@article{Zhang2026Identification,
  author = {Zhang, Lushuang and Jing, Changfeng and Zhou, Ziyi and Wan, Hong},
  title = {Identification of phenology-aligned sensitive windows to extreme-rainfall events for maize in north China Plain and actionable irrigation–drainage triggers},
  journal = {Agricultural Water Management},
  year = {2026},
  doi = {10.1016/j.agwat.2026.110722},
  url = {https://doi.org/10.1016/j.agwat.2026.110722}
}