Reliable estimation of forest carbon fluxes in space and time is a major challenge. Sun-Induced Chlorophyll Fluorescence (SIF) has been found closely linked to vegetation photosynthetic activity. But the application of SIF for direct estimation of Gross Primary Productivity (GPP) is not well investigated. In this study, we demonstrate the estimation of GPP for tropical deciduous forests located in North Western Himalayan Foothills in India using simulated SIF and fluorescence quantum yield (ФF) through a modified Light Use Efficiency (LUEf) model. SIF simulated using Soil Canopy Observation, Photochemistry, and Energy fluxes (SCOPE) model provided the estimate of Photosynthetically Active Radiation (PAR) intercepted by the canopy foliage and ФF. ФF, measured through the Pulse-Amplitude Modulated (PAM) fluorometer quantifies the emission rate of SIF per unit of the absorbed photon. The integration of these factors into the proposed LUEf model offered real-time photosynthetic efficiency and improved the estimate of GPP of the deciduous forest. The results show that GPP estimated from SIF (SIF_TOC) was closely related to GPP_Eddy with R² = 0.91 (p<0.05) with RMSE= 29.24 gC m⁻² month⁻¹ than GPP estimated from LUE model (R²=0. 79, p<0.05) and RMSE = 96.25 gC m⁻² month⁻¹). GPP_MODIS underestimated the GPP with a non-significant correlation to GPP_Eddy for all the months with R²=0. 36 (p<0.05) and RMSE = 188.96 gC m⁻² month⁻¹. The results obtained are promising and the proposed model can be used for estimating carbon fluxes of forests over a larger spatial scale using satellite-derived SIF.

可靠地估算森林的时空碳通量是一项重大挑战。已经发现太阳诱导的叶绿素荧光（SIF）与植被的光合作用密切相关。但是，人们还没有很好地研究SIF在直接估算总初级生产力（GPP）中的应用。在这项研究中，我们通过改进的光利用效率（LUEf）模型，通过模拟SIF和荧光量子产率（ФF），证明了印度喜马拉雅山麓西北部热带落叶林的GPP估算。使用土壤冠层观测，光化学和能量通量（SCOPE）模型模拟​​的SIF提供了被冠层叶子和ФF截获的光合有效辐射（PAR）的估计。ФF，通过脉冲幅度调制（PAM）荧光计测量的SIF可以量化每单位吸收光子的SIF发射速率。将这些因素整合到拟议的LUEf模型中可提供实时的光合作用效率，并改善了落叶林GPP的估算。结果表明GPP是根据SIF（SIF_TOC）与GPP_涡旋密切相关，R ²  = 0.91（p <0.05），RMSE = 29.24 gC m - ²月^-1，比LUE模型估计的GPP（R ² = 0。79 ，p <0.05）和RMSE = 96.25 gC m - ²月^-1）。在R ² = 0的所有月份中，GPP _MODIS均低估了GPP与GPP _Eddy的关系。36（p <0.05）和RMSE = 188.96 gC m - ²月^-1。所获得的结果是有希望的，并且所提出的模型可以用于使用卫星衍生的SIF估计较大空间尺度上的森林碳通量。