Prediction of Open Woodland Transpiration Incorporating Sun-Induced Chlorophyll Fluorescence and Vegetation Structure

Abstract

Transpiration (T) represents plant water use, while sun-induced chlorophyll fluorescence (SIF) emitted during photosynthesis, relates well to gross primary production. SIF can be influenced by vegetation structure, while uncertainties remain on how this might impact the relationship between SIF and T, especially for open and sparse woodlands. In this study, a method was developed to map T in riverine floodplain open woodland environments using satellite data coupled with a radiative transfer model (RTM). Specifically, we used FluorFLiES, a three-dimensional SIF RTM, to simulate the full spectrum of SIF for three open woodland sites with varying fractional vegetation cover. Five specific SIF bands were selected to quantify their correlation with field measured T derived from sap flow sensors. The coefficient of determination of the simulated far-red SIF and field measured T at a monthly scale was 0.93. However, when comparing red SIF from leaf scale to canopy scale to predict T, performance declined by 24%. In addition, varying soil reflectance and understory leaf area index had little effect on the correlation between SIF and T. The method developed can be applied regionally to predict tree water use using remotely sensed SIF datasets in areas of low data availability or accessibility.