Context and objectives
In recent years, satellite observations of SIF have been used to derive photosynthetic activity. Given that photosynthesis and transpiration are synchronized through the opening and closing of the stomata, we hypothesise that SIF data may be valuable to diagnose ecosystem transpiration. Here we propose to exploit the potential SIF observations to derive vegetation stress, and transpiration. Objectives:
- To show the potential of SIF to reflect vegetation stress in relation to transpiration.
- To conform a dataset of transpiration and drought stress incorporating SIF.
We showed unequivocally that SIF and transpiration are closely empirically related. Findings showed that the
best way to estimate vegetation stress from eddy-covariance data is based on a radiation-based or Priestley
and Taylor framework for estimating potential evaporation, calibrated per biome. SIF/PAR can successfully be
used to assess this vegetation stress, outperforming complex land surface models. Based on this SIF-based
vegetation stress product, global maps of transpiration were achieved through direct estimation of
transpiration as well as from assimilation in GLEAM, although the performance of the latter requires further
Products and Services
In this exploration project, the main focus was on building the scientific background of the relationship between
SIF and transpiration or vegetation stress. In the near future, a new high- resolution version of GLEAM will be
developed and made available that incorporates the insights of the project.
Potential users of GLEAM involve both researchers worldwide studying global and local Hydrology, but also
agricultural agents and local governments requiring high-resolution data of ecosystem water use.
|Project leader(s):||UGent - Laboratory of Hydrology and water management (LHWM)|