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Title: Improved mapping carbon, water, and energy land-surface fluxes using remotely sensed indicators of canopy light use efficiency

Author
item Schull, Mitchell
item Anderson, Martha
item Kustas, William - Bill
item Cammalleri, Carmelo
item HOUBORG, RASMUS - Collaborator

Submitted to: American Geophysical Union
Publication Type: Abstract Only
Publication Acceptance Date: 10/18/2012
Publication Date: 12/3/2012
Citation: Schull, M.A., Anderson, M.C., Kustas, W.P., Cammalleri, C.N., Houborg, R. 2012. Improved mapping carbon, water, and energy land-surface fluxes using remotely sensed indicators of canopy light use efficiency [abstract]. American Geophysical Union, December 3-7, 2012, San Francisco, CA.

Interpretive Summary:

Technical Abstract: A light-use-efficiency (LUE) based model of canopy resistance has been embedded into a thermal-based Two-Source Energy Balance (TSEB) model to facilitate coupled simulations of transpiration and carbon assimilation. The model assumes that deviations of the observed canopy LUE from a nominal stand-level value (LUEn – typically indexed by vegetation class) are due to varying conditions of light, humidity, carbon dioxide (CO2) concentration and leaf temperature. The deviations are accommodated by adjusting an effective LUE that responds to the varying conditions. The challenge to monitoring fluxes on a larger scale is to capture the physiological responses due to changing conditions. This challenge can be met using remotely sensed leaf chlorophyll (Cab). Since Cab is a vital pigment for absorbing light for use in photosynthesis, it has been recognized as a key parameter for quantifying photosynthetic functioning that are sensitive to these conditions. Recent studies have shown that it is sensitive to changes in LUE, which defines how efficiently a plant can assimilate CO2 given the absorbed Photosynthetically Active Radiation (PAR) and is therefore useful for monitoring carbon fluxes. We investigate the feasibility of leaf chlorophyll to capture these variations in LUEn using remotely sensed data. To retrieve Cab from remotely sensed data we use the REGularized canopy reFLECtance (REGFLEC) model, a physically based tool that translates at-sensor radiances in the green, red and near infrared spectral regions from multiple satellite sensors into realistic maps of leaf area index and Cab. Initial results show that Cab is exponentially correlated to light use efficiency. Incorporating nominal light use efficiency estimated from Cab is shown to improve fluxes of carbon, water and energy most notably in times of stressed vegetation. The result illustrates that Cab is sensitive to changes in plant physiology and can capture plant stress needed for improved estimation of fluxes. The observed relationship and initial results demonstrate the need for integrating remotely sensed Cab to facilitate improved mapping of coupled carbon, water, and energy fluxes across vegetated landscapes.