Accurate estimation of actual evapotranspiration (ETa) is crucial for irrigation management. The standard FAO-56 dual-crop coefficient model often leads to biases under specific regional conditions. This study aimed to estimate ETa using the FAO-56 dual crop coefficient model and compare the estimates against eddy covariance (EC) observations in a typical winter wheat-summer maize rotation system in China’s Yellow River Basin. Using nearly two years of EC data (October 2023-July 2025), we localized key model parameters and assessed model performance across hourly, daily, and monthly scales. Optimized parameters for winter wheat (mid-term crop coefficient (Kcb mid), maximum evaporation coefficient (Kc−max), total evaporable water (TEW), readily evaporable water (REW)) were 1.05, 1.00, 15 mm, and 6 mm, respectively; for summer maize: 1.00, 0.85, 9 mm, and 4 mm. Localization reduced root mean square error (RMSE) by 44.8%. Model performance was best at the monthly scale (coefficient of determination R²=0.45, normalized RMSE nRMSE = 15%), followed by daily (R²=0.29, nRMSE = 26%). Due to structural limitations, the hourly scale showed large errors (nRMSE = 130%) and is not recommended for real-time monitoring. Cumulative ETa errors decreased substantially after localization, with an 89.1% reduction during the 2024 summer maize season. This study provides a reliable localized parameter set and scale-specific guidance for precision water management in the Yellow River Basin and similar climatic regions. Graphical Abstract This visual summary provides a concise overview of a study that localized the FAO-56 dual crop coefficient model for a winter wheat–summer maize rotation system in China’s Yellow River Basin. Eddy covariance observations were used to iteratively calibrate key parameters including basal crop coefficients, maximum evaporation coefficient, and soil evaporation parameters (total evaporable water (TEW) and readily evaporable water (REW)). The graphical abstract illustrates the study site, methodological workflow, model structure, and key performance improvements. Following localization, daily-scale root mean square error (RMSE) decreased by 44.8%, and cumulative evapotranspiration error during the summer maize season was reduced by 89.1%. Multi-scale validation revealed that the model performs best at monthly scale (nRMSE = 15%) and is suitable for daily irrigation scheduling but not recommended for hourly real-time monitoring. This graphical abstract highlights the study’s core contribution: a region-specific parameter set and clear temporal-scale application boundaries that support precision water management in similar agroecosystems.

Localization of Parameters for the FAO-56 Dual Crop Coefficient Model and Multi-temporal Scale Effects in Winter Wheat-summer Maize Rotation Systems

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发表日期：

2026年7月3日

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Lintong Gui,
Shengqi Jian,
Asaad Y. Shamseldin

摘要

Accurate estimation of actual evapotranspiration (ET_a) is crucial for irrigation management. The standard FAO-56 dual-crop coefficient model often leads to biases under specific regional conditions. This study aimed to estimate ET_a using the FAO-56 dual crop coefficient model and compare the estimates against eddy covariance (EC) observations in a typical winter wheat-summer maize rotation system in China’s Yellow River Basin. Using nearly two years of EC data (October 2023-July 2025), we localized key model parameters and assessed model performance across hourly, daily, and monthly scales. Optimized parameters for winter wheat (mid-term crop coefficient (K_{cb mid}), maximum evaporation coefficient (K_c−max), total evaporable water (TEW), readily evaporable water (REW)) were 1.05, 1.00, 15 mm, and 6 mm, respectively; for summer maize: 1.00, 0.85, 9 mm, and 4 mm. Localization reduced root mean square error (RMSE) by 44.8%. Model performance was best at the monthly scale (coefficient of determination R²=0.45, normalized RMSE nRMSE = 15%), followed by daily (R²=0.29, nRMSE = 26%). Due to structural limitations, the hourly scale showed large errors (nRMSE = 130%) and is not recommended for real-time monitoring. Cumulative ET_a errors decreased substantially after localization, with an 89.1% reduction during the 2024 summer maize season. This study provides a reliable localized parameter set and scale-specific guidance for precision water management in the Yellow River Basin and similar climatic regions.

Graphical Abstract

This visual summary provides a concise overview of a study that localized the FAO-56 dual crop coefficient model for a winter wheat–summer maize rotation system in China’s Yellow River Basin. Eddy covariance observations were used to iteratively calibrate key parameters including basal crop coefficients, maximum evaporation coefficient, and soil evaporation parameters (total evaporable water (TEW) and readily evaporable water (REW)). The graphical abstract illustrates the study site, methodological workflow, model structure, and key performance improvements. Following localization, daily-scale root mean square error (RMSE) decreased by 44.8%, and cumulative evapotranspiration error during the summer maize season was reduced by 89.1%. Multi-scale validation revealed that the model performs best at monthly scale (nRMSE = 15%) and is suitable for daily irrigation scheduling but not recommended for hourly real-time monitoring. This graphical abstract highlights the study’s core contribution: a region-specific parameter set and clear temporal-scale application boundaries that support precision water management in similar agroecosystems.