Wheat crop models underestimate drought stress in semi-arid and Mediterranean environments

Under climate change and increasingly extreme weather, projections of water demand and drought stress from process-based crop models can inform risk management and adaptation strategies. Previous studies investigating maize crop models demonstrated considerable error in the simulation of water use, and no similar evaluation of wheat crop models exists. The aims of this study were to (1) evaluate wheat crop models’ performance in reproducing observed daily evapotranspiration (ET) for Mediterranean and semi-arid environments, and (2) identify factors and processes associated with model error and uncertainty. These were assessed with an ensemble of wheat crop models for two experiments, one conducted in Bushland, Texas, USA (three seasons, deficit and full irrigation) and another in Avignon, France (four rainfed seasons) with winter bread and durum wheat, respectively. Models were calibrated with all observed data for crop growth. The model ensemble median underestimated water use in all environments evaluated, suggesting a systematic bias. The relative error in underestimating daily ET was constant across levels of atmospheric evaporative demand; therefore, the absolute error was greater for days with larger evaporative demand. This implies errors in the soil water balance increase more rapidly under high evaporative demand conditions. Using a potential versus reference crop evapotranspiration approach did not explain relative model performance. However, the sensitivity analysis indicated that simulation of atmospheric evaporative demand terms explained much more uncertainty in seasonal water use than terms related to soil depth or root growth. Errors in simulated leaf area index were associated with errors in daily simulated ET, but the relationship varied with the growth stage. Collectively, the results suggest the need to improve simulation of atmospheric ET demand to avoid underestimating projected impacts of drought or required water resource availability for viable production systems.

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Publication Details

Journal
Field Crops Research
Published
2025-06-13
DOI
https://doi.org/10.1016/j.fcr.2025.110032
Citations
6
Primary Topic
Climate change impacts on agriculture
Type
article
Field-Weighted Citation Impact
18.16

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article

Wheat crop models underestimate drought stress in semi-arid and Mediterranean environments

Alfredo Rodríguez, Tobias K. D. Weber, Efstathios Diamantopoulos, Kelly Robert Thorp et al.
6 citations
Field Crops Research
Climate change impacts on agriculture
18.16
article

Wheat crop models underestimate drought stress in semi-arid and Mediterranean environments

Alfredo Rodríguez, Tobias K. D. Weber, Efstathios Diamantopoulos, Kelly Robert Thorp, Steven R. Evett, Senthold Asseng, Jean L. Steiner, Heidi Webber, Iwan Supit, Pierre Martre, Guillaume Jégo, Roberto Ferrise, Elizabeth Pattey, Gerrit Hoogenboom, Margarita Ruiz‐Ramos, Albert Olioso, Sébastien Garrigues, Vakhtang Shelia, Bruce A. Kimball, F. Ewert, Mohan Viswanathan, Thomas Gaiser, Marianne Crépeau, Gloria Padovan, André Chanzy, John White, Jose Rafael Guarin, Davide Cammarano, Amit Kumar Srivastava, Tony Hunt, Chao Wang, Yi Chen, Dominique Ripoche, Yujing Gao, S. Gayler, K.S. Copeland, David Cooke, Fulu Tao
article en
6 citations

Abstract

Under climate change and increasingly extreme weather, projections of water demand and drought stress from process-based crop models can inform risk management and adaptation strategies. Previous studies investigating maize crop models demonstrated considerable error in the simulation of water use, and no similar evaluation of wheat crop models exists. The aims of this study were to (1) evaluate wheat crop models’ performance in reproducing observed daily evapotranspiration (ET) for Mediterranean and semi-arid environments, and (2) identify factors and processes associated with model error and uncertainty. These were assessed with an ensemble of wheat crop models for two experiments, one conducted in Bushland, Texas, USA (three seasons, deficit and full irrigation) and another in Avignon, France (four rainfed seasons) with winter bread and durum wheat, respectively. Models were calibrated with all observed data for crop growth. The model ensemble median underestimated water use in all environments evaluated, suggesting a systematic bias. The relative error in underestimating daily ET was constant across levels of atmospheric evaporative demand; therefore, the absolute error was greater for days with larger evaporative demand. This implies errors in the soil water balance increase more rapidly under high evaporative demand conditions. Using a potential versus reference crop evapotranspiration approach did not explain relative model performance. However, the sensitivity analysis indicated that simulation of atmospheric evaporative demand terms explained much more uncertainty in seasonal water use than terms related to soil depth or root growth. Errors in simulated leaf area index were associated with errors in daily simulated ET, but the relationship varied with the growth stage. Collectively, the results suggest the need to improve simulation of atmospheric ET demand to avoid underestimating projected impacts of drought or required water resource availability for viable production systems.

Field Crops ResearchVol. 332
New Mexico State University (US), University of Hohenheim (DE), Goddard Institute for Space Studies (US), Agricultural Research Service (US), Julius Kühn-Institut (DE), Agriculture and Agri-Food Canada (CA), University of Bonn (DE), European Centre for Medium-Range Weather Forecasts (GB), State Grid Corporation of China (China) (CN), Kansas State University (US), Chinese Academy of Sciences (CN), Université d'Avignon et des Pays de Vaucluse (FR), Université de Montpellier (FR), Aarhus University (DK), Institut Agro Montpellier (FR), University of Florida (US), Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement (FR), Leibniz Centre for Agricultural Landscape Research (DE), Écologie des Forêts Méditerranéennes (FR), Laboratoire d'Ecophysiologie des Plantes sous Stress environnementaux (FR), Institut Agro Montpelier (FR), U.S. Arid Land Agricultural Research Center (US), Brandenburg University of Applied Sciences (DE), Conservation and Production Research Laboratory (US), Institute of Geographic Sciences and Natural Resources Research (CN), University of Chinese Academy of Sciences (CN), EMMAH - Environnement Méditerranéen et Modélisation des Agro-Hydrosystèmes, University of Florence (IT), Brandenburg University of Technology Cottbus-Senftenberg (DE), University of Bayreuth (DE), Technical University of Munich (DE), University of Castilla-La Mancha (ES), University of Guelph (CA), Wageningen University & Research (NL)
Deutsche Forschungsgemeinschaft, Agricultural Research Service, Leibniz-Gemeinschaft
Climate action
Openalex Percentile: Top 1%
Climate change impacts on agriculture
18.16
DOIOpen Access PDFOpenAlex
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