Chevuru et al. (2026) Global Gridded Climate-Responsive Crop Selection: Sowing Dates and Crop Varieties in a Warming World

Identification

• Journal: Scientific Data
• Year: 2026
• Date: 2026-04-03
• Authors: Sneha Chevuru, Rens L. P. H. van Beek, M. Robert P. Van Vliet, Marc F. P. Bierkens
• DOI: 10.1038/s41597-026-07164-9

Research Groups

• Department of Physical Geography, Utrecht University, Utrecht, The Netherlands
• Unit Subsurface & Groundwater Systems, Deltares, Utrecht, The Netherlands

Short Summary

This paper presents a global gridded dataset of simulated crop yields and consumptive water use for multiple crop varieties and sowing dates, developed to support assessments of future crop production and adaptation strategies under climate change. The dataset covers five major crops from 1961 to 2100, enabling the identification of climate-responsive crop selections.

Objective

• To develop a global gridded dataset providing simulated yields and consumptive water use for multiple crop varieties and sowing dates for maize, soybean, winter wheat, spring wheat, and rice, to support assessments of future crop production under climate change.

Study Configuration

• Spatial Scale: Global, gridded at 0.5 degrees by 0.5 degrees (approximately 55 kilometers at the equator), covering 64,055 land grid cells (excluding Greenland).
• Temporal Scale: 1961 to 2100.

Methodology and Data

• Models used: WOrld FOod STudies (WOFOST) crop growth model. Simulations were performed under five global climate models and three greenhouse gas concentration scenarios.
• Data sources:
  • Climate forcing data: Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) database.
  • Crop calendar information: AgMIP-GGCMI crop calendars repository.
  • Crop cultivar parameters: WOFOST crop parameter repository.
  • Soil properties: FAO Digital Soil Map of the World (DSMW).

Main Results

• A comprehensive global gridded dataset was developed, providing simulated yields and consumptive water use for maize, soybean, winter wheat, spring wheat, and two rice varieties.
• The dataset offers simulations for multiple crop varieties and sowing dates, allowing for the identification of optimal climate-responsive crop selections.
• The data covers a historical period (1961-present) and future projections up to 2100, at a spatial resolution of 0.5 degrees by 0.5 degrees.

Contributions

• This article provides a novel, globally gridded dataset that explicitly incorporates the impact of varying sowing dates and crop varieties on yields and water use under future climate change scenarios.
• It offers a valuable resource for crop modeling, climate impact assessments, and agricultural adaptation planning by enabling detailed analysis of climate-responsive crop selection strategies.
• The dataset facilitates identifying suitable crop varieties and planting dates to sustain yields and optimize water use in a warming world, addressing a critical gap in existing literature.

Funding

• European Union Horizon Programme GoNexus project (Grant Agreement Number 101003722)
• Netherlands Scientific Organisation (NWO) VIDI grant (VI.Vidi.193.019)
• European Research Council (ERC) under the European Union’s Horizon Europe research and innovation program (grant agreement 101039426 B-WEX)
• NWO for the national supercomputer Snellius (project no. EINF-11826)

Citation

@article{Chevuru2026Global,
  author = {Chevuru, Sneha and Beek, Rens L. P. H. van and Vliet, M. Robert P. Van and Bierkens, Marc F. P.},
  title = {Global Gridded Climate-Responsive Crop Selection: Sowing Dates and Crop Varieties in a Warming World},
  journal = {Scientific Data},
  year = {2026},
  doi = {10.1038/s41597-026-07164-9},
  url = {https://doi.org/10.1038/s41597-026-07164-9}
}