Giri et al. (2026) Quantifying waterlogging effects on crop production at different spatial scales

Identification

• Journal: Agricultural and Forest Meteorology
• Year: 2026
• Date: 2026-07-15
• Authors: Surendra Giri, M. Palka, Leonardo Inforsato, Gohar Ghazaryan, Claas Nendel
• DOI: 10.1016/j.agrformet.2026.111350

Research Groups

• Leibniz Centre for Agricultural Landscape Research (ZALF)
• Institute of Biochemistry and Biology, University of Potsdam
• Institute of Geography, Humboldt-Universität zu Berlin
• Global Change Research Institute of the Czech Academy of Sciences

Short Summary

This study aims to detect waterlogging at the sub-field scale using remote sensing and quantify associated yield losses using a process-based crop model. The results show that crops in waterlogged areas exhibit vegetation indices 42% (triticale) to 61% (oilseed rape) lower than in non-waterlogged areas, particularly during early growth stages.

Objective

• Investigate the impact of waterlogging on crop production at different spatial scales using a combination of remote sensing and process-based crop modelling.

Study Configuration

• Spatial Scale: Field scale, regional scale
• Temporal Scale: 2023-2024 growing season

Methodology and Data

• Models used: MONICA (Model for Nitrogen and Carbon Dynamics in Agroecosystems) crop model
• Data sources: Sentinel-1 SAR data, Sentinel-2 multispectral data, ERA5 reanalysis data

Main Results

• Waterlogging was detected using a Sentinel-1 SAR-based classification framework combining Edge–Otsu thresholding and Log-cumulant Gamma Markov Random Field (LGM) at the field scale.
• Crops in waterlogged areas exhibited vegetation indices 42% (triticale) to 61% (oilseed rape) lower than in non-waterlogged areas, particularly during early growth stages.
• MONICA simulations showed a mean yield decrease of 22.6% for winter wheat under waterlogging conditions.

Contributions

• This study provides a novel approach to detecting waterlogging at the sub-field scale using remote sensing and quantifying associated yield losses using a process-based crop model.
• The results highlight the importance of considering terrain-driven redistribution of water in simulating waterlogging impacts on crop yields.

Funding

• European Space Agency (ESA) Copernicus program
• Leibniz Centre for Agricultural Landscape Research (ZALF)
• German Federal Ministry of Education and Research (BMBF)

Citation

@article{Giri2026Quantifying,
  author = {Giri, Surendra and Palka, M. and Inforsato, Leonardo and Ghazaryan, Gohar and Nendel, Claas},
  title = {Quantifying waterlogging effects on crop production at different spatial scales},
  journal = {Agricultural and Forest Meteorology},
  year = {2026},
  doi = {10.1016/j.agrformet.2026.111350},
  url = {https://doi.org/10.1016/j.agrformet.2026.111350}
}