4.7 Article

Global assessment of partitioning transpiration from evapotranspiration based on satellite solar-induced chlorophyll fluorescence data

Journal

JOURNAL OF HYDROLOGY
Volume 612, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.jhydrol.2022.128044

Keywords

Evapotranspiration partitioning; Transpiration estimation; Solar-induced chlorophyll fluorescence; Stomatal conductance; Penman-Monteith model

Funding

  1. National Natural Science Foundation of China (NSFC) [42125105, 42071388]
  2. NSFC [42101320]

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Accurately assessing terrestrial ecosystem transpiration (T) is crucial for understanding vegetation-atmosphere interactions under climate change. This study explores the potential of solar-induced chlorophyll fluorescence (SIF) in estimating T. Using a combination of satellite SIF data and ground observations, a model is developed to estimate T for different plant functional types (PFTs). Results show a strong relationship between SIF and the product of canopy conductance and vapor pressure deficit. The estimated T/ET ratio is consistent with other methods, indicating the robustness of the approach. This method provides valuable insights into ecohydrological processes and can be a useful tool for T and ET estimation using remote sensing.
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 (g(c)) 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 (g(c) x VPD0.5) is tighter than the relationship between SIF and ecosystem productivity. The SIF-g(c) x VPD0.5 linear regressions show improved R-2 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 (R-2 = 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.

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