Global assessment of partitioning transpiration from evapotranspiration based on satellite solar-induced chlorophyll fluorescence data
Résumé
An accurate assessment of terrestrial ecosystem transpiration (T) is important to understand the vegetation-atmosphere feedbacks under climate change. Solar-induced chlorophyll fluorescence (SIF) shows great potential to estimate T because of its mechanical linkage with photosynthesis and stomatal conductance. However, a global and spatially estimation of terrestrial T based on remotely sensed SIF remains unresolved and novel strategies are challenged to entail a precise partition of T from evapotranspiration (ET) across various biomes. Here, with far-red SIF from Sentinel-5 Precursor satellite and ground observations for a total of 30 sites encompassing ten primary plant functional types (PFTs), we extend a SIF-driven semi-mechanism canopy conductance (gc) model for different plant functional types (PFTs), and use the optimized Penman-Monteith model (PMopt) to calculate T and T/ET. We reveal that the relationship between SIF and the product of gc and 0.5 power of vapor pressure deficit (gc × VPD0.5) is tighter than the relationship between SIF and ecosystem productivity. The SIF-gc × VPD0.5 linear regressions show improved R2 and increased magnitude in slopes across PFTs when aggregating daily to 16-day. Our T/ET results show high correlations with the results of the Ball-Berry-Leuning model combined with PMopt at the site scale (R2 = 0.69), and with the results calculated by leaf area index in a previous study at the PFT scale (0.70). We further determine the global mean T/ET (0.57 ± 0.14), close to the ensemble mean of global averaged T/ET (0.55), using 36 different methods. The global T estimated using the SIF-based approach is compared with two other remote sensing products. Our method provides a valuable tool for T and ET estimation using remote sensing data and is critical to understanding ecohydrological processes under climate change.
Auteurs, date et publication :
Auteurs Yaojie Liu , Yongguang Zhang , Nan Shan , Zhaoying Zhang , Zhongwang Wei
Publication : Journal of Hydrology
Date : 2022
Volume : 612
Pages : 128044