Articles | Volume 18, issue 21
https://doi.org/10.5194/gmd-18-8379-2025
https://doi.org/10.5194/gmd-18-8379-2025
Development and technical paper
 | 
10 Nov 2025
Development and technical paper |  | 10 Nov 2025

Modeling wheat development under extreme weather with WOFOST-EW v1

Jinhui Zheng, Le Yu, Zhenrong Du, Liujun Xiao, and Xiaomeng Huang

Viewed

Total article views: 2,066 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
1,422 565 79 2,066 121 71 91
  • HTML: 1,422
  • PDF: 565
  • XML: 79
  • Total: 2,066
  • Supplement: 121
  • BibTeX: 71
  • EndNote: 91
Views and downloads (calculated since 25 Feb 2025)
Cumulative views and downloads (calculated since 25 Feb 2025)

Viewed (geographical distribution)

Total article views: 2,066 (including HTML, PDF, and XML) Thereof 2,027 with geography defined and 39 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 16 Mar 2026
Download
Short summary
This study integrates the extreme weather index and deep learning algorithms with the World Food Studies Simulation Model (WOFOST), proposing the WOFOST-EW v1. WOFOST-EW significantly improves the simulation of winter wheat growth under extreme weather conditions, providing more accurate predictions of phenology and yield. As extreme weather events become more frequent, WOFOST-EW provides a key tool for agricultural development.
Share