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Related Experiment Video

Updated: Apr 21, 2026

Surface Renewal: An Advanced Micrometeorological Method for Measuring and Processing Field-Scale Energy Flux Density Data
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[Calculating method for crop water requirement based on air temperature].

Guo-Tong Tao, Jing-Lei Wang, Ji-Qin Nan

    Ying Yong Sheng Tai Xue Bao = the Journal of Applied Ecology
    |October 28, 2014
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    Summary

    Accurate crop water requirement (ETc) estimation is vital for irrigation forecasting. This study developed a model using only air temperature to predict ETc, achieving high accuracy across various time scales for better water resource management.

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    Area of Science:

    • Agricultural Science
    • Hydrology
    • Meteorology

    Background:

    • Accurate crop water requirement (ETc) estimation is crucial for effective irrigation forecasting and agricultural water management.
    • Current methods often rely on extensive meteorological data, which are not always available quantitatively in forecasts, except for air temperature.
    • This limitation necessitates exploring methods for precise ETc estimation using limited, readily available data like air temperature.

    Purpose of the Study:

    • To explore precise estimation of crop evapotranspiration (ETc) using only air temperature data for irrigation forecasting.
    • To investigate the accuracy of ETc estimation based on different time scales (1, 3, and 7 days).
    • To provide a basis for improved local irrigation forecasts and optimal management of water and soil resources.

    Main Methods:

    • Corrected parameters for the Hargreaves and McClound equations using meteorological data from 1970-2010.
    • Selected the Hargreaves equation to calculate reference evapotranspiration (ET0) for winter wheat.
    • Developed a model combining the Hargreaves equation and a crop coefficient model based on air temperature to predict ETc at 1, 3, and 7-day intervals.

    Main Results:

    • The developed model showed high correlation coefficients between measured and predicted ETc: 0.883 (1-day), 0.933 (3-day), and 0.959 (7-day).
    • Consistency indexes ranged from 0.94 to 0.97, indicating reduced forecast error with increasing time scales.
    • Forecast accuracy exceeded 80% with errors less than 1 mm/day and 90% with errors less than 2 mm/day.

    Conclusions:

    • The model provides a reliable method for estimating crop water requirement using only air temperature.
    • Forecast accuracy improves with longer time scales, making it suitable for irrigation planning.
    • The study offers a sound basis for enhancing irrigation forecasting and agricultural management in irrigated regions.