Transpiration is one of the most important surface water fluxes, but current estimates vary widely. Accurate estimates of transpiration are essential as they control plant water use and its…

This is a $412,164 grant awarded by the National Aeronautics and Space Administration (NASA) to The Trustees of Columbia University in the City of New York, operating as Columbia University, to develop a new remote sensing-based algorithm for estimating plant transpiration. The objective is to improve the partitioning of evapotranspiration and provide better estimates of plant water use efficiency, which is essential for understanding the water and carbon cycles. The research will leverage satellite-based observations of solar-induced fluorescence and atmospheric isotopic oxygen composition to constrain the transpiration estimates, which will be validated against eddy covariance flux measurements and the SapFluxNet global dataset. This work is intended to support land surface model development and drought monitoring. The grant does not have a set-aside designation and is part of Columbia University's broader portfolio of federal research contracts and grants, which includes work with the Department of Defense, Department of Energy, and other agencies across a range of scientific and technical domains.

Transpiration is one of the most important surface water fluxes, but current estimates vary widely. Accurate estimates of transpiration are essential as they control plant water use and its efficiency, and as such connect the water cycle to the carbon cycle but also because they can provide estimates of plants' resilience to droughts.we propose to develop a new remote sensing based algorithm to better estimate the partitioning of evapotranspiration towards transpiration. At present very few constrained estimates of transpiration exist. We propose to build on a recent machine-learning estimate of evapotranspiration based on only remote sensing data, named wecann [alemohammad ET AL., 2016] to estimate transpiration. To constrain transpiration during the learning process we will use two main products: 1) gome-2 solar-induced fluorescence, an indicator of plant gross primary productivity, thus directly to the rate of plant trasnpiration through leaf gas exchange and 2) isotopic oxygen atmospheric composition, an indicator of surface water partitioning. The retrieval will be tested and validated against 1) eddy-covariance flux measurements using the concept of underlying water use efficiency (relating transpiration to GPP) and against a new product called 2) sapfluxnet: a collection of sapflow record across the globe. The new product will be an essential tool for land-surface model developement and for drought monitoring.