Abstract Terrestrial evapotranspiration (ET) is an important flux that links global cycles of carbon, water and energy and is largely driven by transpiration (T) through leaf stomata in vegetated areas during the growing season. ET, however, remains one of the most uncertain hydrological variables at the global scale. In this study, we proposed a semi-mechanistic model for estimating terrestrial T by deriving an analytical solution between solar-induced chlorophyll fluorescence (SIF) and stomatal conductance (gc) as well as vapor pressure deficit (VPD), combining theories on the photosynthetic pathway and optimal stomatal behavior. The relationships of SIF-ETR and ETR-gc·VPD0.5 was calibrated by the Soil-Canopy Observation of Photosynthesis and Energy (SCOPE) model. This model was validated by hourly canopy SIF and concurrent eddy covariance flux observations at both forest and cropland ecosystems. Results showed that the SIF combined with VPD can better predict gc than using SIF alone with a more consistent seasonal trends found in both SIF and gc·VPD0.5. The correlation between gc·VPD0.5 and SIF was stronger than those between gc and SIF and between gc and VIs. Canopy T was accurately predicted from SIF at both hourly (R2 > 0.65) and daily (R2 > 0.76) scales and was also successfully estimated using SIF observations from the TROPOspheric Monitoring Instrument (TROPOMI) at cropland ecosystems. In comparison with empirical relationships of directly linking gc with SIF or VIs, the proposed model produced latent heat flux (λE) estimation in best agreement with measured values at all three sites. Our model could be a step forward in understanding the coupling of carbon and water cycles and may be used in ecosystem models for improving ET estimation over large areas.

中文翻译：

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从遥感太阳诱导叶绿素荧光估算蒸腾作用的模型

摘要 陆地蒸散量（ET）是连接全球碳、水和能量循环的重要通量，主要由生长季节通过植被区叶气孔的蒸腾作用（T）驱动。然而，ET 仍然是全球范围内最不确定的水文变量之一。在这项研究中，我们结合光合作用的理论，通过推导出太阳诱导的叶绿素荧光 (SIF) 和气孔导度 (gc) 以及蒸汽压亏缺 (VPD) 之间的解析解，提出了一种估算陆地 T 的半机械模型。路径和最佳气孔行为。SIF-ETR与ETR-gc·VPD0.5的关系通过土壤冠层光合作用和能量观测（SCOPE）模型进行标定。该模型通过每小时冠层 SIF 和同时在森林和农田生态系统中的涡流协方差通量观测进行验证。结果表明，与单独使用 SIF 相比，SIF 与 VPD 相结合可以更好地预测 gc，在 SIF 和 gc·VPD0.5 中都发现了更一致的季节性趋势。gc·VPD0.5与SIF之间的相关性强于gc与SIF之间以及gc与VIs之间的相关性。冠层 T 在每小时 (R2 > 0.65) 和每日 (R2 > 0.76) 尺度上都由 SIF 准确预测，并且还使用来自农田生态系统的对流层监测仪器 (TROPOMI) 的 SIF 观测成功估计。与直接将 gc 与 SIF 或 VI 联系起来的经验关系相比，所提出的模型产生的潜热通量 (λE) 估计与所有三个站点的测量值最一致。