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<p>Optimizing water use requires a comprehensive understanding of crop evapotranspiration (ET). Stomatal conductance, soil moisture, and weather greatly influence ET. However, there are a few studies, if any, that have studied the spatial variation of ET derived from on-field conductance observations. The present study utilizes the Penman-Monteith equation along with the conductance observations to account for the spatial variation in ET. These conductance-based ET estimates (ET<sub>a−Con</sub>) are compared with the ET values (ET<sub>c−PM</sub>) estimated using the dual crop coefficient-based FAO Penman-Monteith (FAO P-M). Also, ET values are derived from a straightforward but novel method using the soil moisture depletion (ET<sub>a−SMD</sub>) data and used for comparison. These methods estimate ET for five irrigation treatments. The study examines wheat crops under varying irrigation treatments at an experimental site in western Uttar Pradesh, India. The irrigation treatments are drip (fully irrigated), drip (50% maximum allowable deficit (MAD)), flood (50% MAD), farmers’ field replication, and rainfed treatment, with each treatment having four replications. ET<sub>a−SMD</sub> values compared well with the ET<sub>c−PM</sub> estimates for all the treatments except the rainfed treatment. This confirms the potential of using the proposed methodology to accurately capture the spatial variation of ET using soil moisture data. Spatially varied ET<sub>a−Con</sub> values closely align with ET<sub>a−SMD</sub> estimates. The lowest mean absolute error occurs for (0.10&#xa0;mm/day) for ET<sub>a-Con</sub> is found in the drip (fully irrigated) treatment, followed by flood (50% MAD) (0.20&#xa0;mm/day), drip (50% MAD) (0.26&#xa0;mm/day), rainfed (0.30&#xa0;mm/day), and farmers’ field replication (0.37&#xa0;mm/day), respectively. ET<sub>a−Con</sub> estimates are most precise under low water stress. Results suggest that the spatial variation of ET can be accurately assessed using observed conductance data, and conductance-based ET estimates may be a suitable tool for irrigation scheduling.</p>

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Conductance-based evapotranspiration estimates for wheat crops grown under different irrigation treatments

  • 期刊论文

  • 发表日期：

    2025年9月17日

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  • Manoj Yadav,
  • Hitesh Upreti

摘要

Optimizing water use requires a comprehensive understanding of crop evapotranspiration (ET). Stomatal conductance, soil moisture, and weather greatly influence ET. However, there are a few studies, if any, that have studied the spatial variation of ET derived from on-field conductance observations. The present study utilizes the Penman-Monteith equation along with the conductance observations to account for the spatial variation in ET. These conductance-based ET estimates (ETa−Con) are compared with the ET values (ETc−PM) estimated using the dual crop coefficient-based FAO Penman-Monteith (FAO P-M). Also, ET values are derived from a straightforward but novel method using the soil moisture depletion (ETa−SMD) data and used for comparison. These methods estimate ET for five irrigation treatments. The study examines wheat crops under varying irrigation treatments at an experimental site in western Uttar Pradesh, India. The irrigation treatments are drip (fully irrigated), drip (50% maximum allowable deficit (MAD)), flood (50% MAD), farmers’ field replication, and rainfed treatment, with each treatment having four replications. ETa−SMD values compared well with the ETc−PM estimates for all the treatments except the rainfed treatment. This confirms the potential of using the proposed methodology to accurately capture the spatial variation of ET using soil moisture data. Spatially varied ETa−Con values closely align with ETa−SMD estimates. The lowest mean absolute error occurs for (0.10 mm/day) for ETa-Con is found in the drip (fully irrigated) treatment, followed by flood (50% MAD) (0.20 mm/day), drip (50% MAD) (0.26 mm/day), rainfed (0.30 mm/day), and farmers’ field replication (0.37 mm/day), respectively. ETa−Con estimates are most precise under low water stress. Results suggest that the spatial variation of ET can be accurately assessed using observed conductance data, and conductance-based ET estimates may be a suitable tool for irrigation scheduling.