Disentangling sources of errors in simulated wheat evapotranspiration
Abstract
Accurate simulation of crop evapotranspiration (ET) is critical for water management and for understanding the impacts of climate variability and change. Yet evidence on model skill in simulating ET remains limited, and the sources of error remain poorly understood. Daily simulations from 17 wheat crop models were evaluated against field observations from two sites in semi-arid and Mediterranean environments under water-limited and irrigated conditions. Absolute ET errors were larger under irrigation, but this contrast was substantially attenuated after normalization by observed ET. The larger absolute errors under irrigation were mainly associated with a greater lack-of-correlation component rather than stronger systematic bias, indicating greater day-to-day mismatch between simulations and observations. Differences among ET-demand approaches also tended to be more evident under irrigation, with Priestley–Taylor-based models tending to produce larger errors, although the broad method classes also differed in other model components. Mixed-effects attribution showed that the conditional associations between ET error and climatic factors differed between the two water-supply datasets. Under irrigation, ET simulation error was associated with vapour pressure deficit (VPD), wind speed, radiation, and the component of maximum temperature not linearly explained by VPD, whereas under water-limited conditions meteorological attribution was weaker and observed soil–water status provided additional information. Root-zone soil moisture provided greater model support than shallow or deep soil moisture and modified the association between VPD and ET error. These findings identify atmospheric-demand representation and root-zone water availability as priorities for improving the evaluation and development of crop ET simulations.
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BibTeX
@article{wang2026disentangling,
title = {{Disentangling sources of errors in simulated wheat evapotranspiration}},
author = {Chenzhi Wang and Diane Cooke and Xinxin Chen and Jeffrey White and Katja Trachte and Pierre Martre and Senthold Asseng and Frank Ewert and Bruce Kimball and Gerrit Hoogenboom and Steven Evett and André Chanzy and Sébastien Garrigues and Albert Olioso and Karen Copeland and Jean Steiner and Davide Cammarano and Yi Chen and Marianne Crépeau and Roberto Ferrise and Loic Manceau and Thomas Gaiser and Yujing Gao and Sebastian Gayler and Jose Guarin and Tony Hunt and Guillaume Jégo and Gloria Padovan and Elizabeth Pattey and Dominique Ripoche and Alfredo Rodríguez and Margarita Ruiz Ramos and Vakhtang Shelia and Amit Srivastava and Iwan Supit and Fulu Tao and Kelly Thorp and Michelle Viswanathan and Tobias Karl David Weber and Heidi Webber},
journal = {in silico Plants},
year = {2026},
month = sep,
doi = {10.1093/insilicoplants/diag024},
url = {https://hal.inrae.fr/hal-05753810v1},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Disentangling sources of errors in simulated wheat evapotranspiration
AU - Chenzhi Wang
AU - Diane Cooke
AU - Xinxin Chen
AU - Jeffrey White
AU - Katja Trachte
AU - Pierre Martre
AU - Senthold Asseng
AU - Frank Ewert
AU - Bruce Kimball
AU - Gerrit Hoogenboom
AU - Steven Evett
AU - André Chanzy
AU - Sébastien Garrigues
AU - Albert Olioso
AU - Karen Copeland
AU - Jean Steiner
AU - Davide Cammarano
AU - Yi Chen
AU - Marianne Crépeau
AU - Roberto Ferrise
AU - Loic Manceau
AU - Thomas Gaiser
AU - Yujing Gao
AU - Sebastian Gayler
AU - Jose Guarin
AU - Tony Hunt
AU - Guillaume Jégo
AU - Gloria Padovan
AU - Elizabeth Pattey
AU - Dominique Ripoche
AU - Alfredo Rodríguez
AU - Margarita Ruiz Ramos
AU - Vakhtang Shelia
AU - Amit Srivastava
AU - Iwan Supit
AU - Fulu Tao
AU - Kelly Thorp
AU - Michelle Viswanathan
AU - Tobias Karl David Weber
AU - Heidi Webber
PY - 2026
DA - 2026/09/16
JO - in silico Plants
DO - 10.1093/insilicoplants/diag024
UR - https://hal.inrae.fr/hal-05753810v1
AB - Accurate simulation of crop evapotranspiration (ET) is critical for water management and for understanding the impacts of climate variability and change. Yet evidence on model skill in simulating ET remains limited, and the sources of error remain poorly understood. Daily simulations from 17 wheat crop models were evaluated against field observations from two sites in semi-arid and Mediterranean environments under water-limited and irrigated conditions. Absolute ET errors were larger under irrigation, but this contrast was substantially attenuated after normalization by observed ET. The larger absolute errors under irrigation were mainly associated with a greater lack-of-correlation component rather than stronger systematic bias, indicating greater day-to-day mismatch between simulations and observations. Differences among ET-demand approaches also tended to be more evident under irrigation, with Priestley–Taylor-based models tending to produce larger errors, although the broad method classes also differed in other model components. Mixed-effects attribution showed that the conditional associations between ET error and climatic factors differed between the two water-supply datasets. Under irrigation, ET simulation error was associated with vapour pressure deficit (VPD), wind speed, radiation, and the component of maximum temperature not linearly explained by VPD, whereas under water-limited conditions meteorological attribution was weaker and observed soil–water status provided additional information. Root-zone soil moisture provided greater model support than shallow or deep soil moisture and modified the association between VPD and ET error. These findings identify atmospheric-demand representation and root-zone water availability as priorities for improving the evaluation and development of crop ET simulations.
SN - 2517-5025
ER -