Articles | Volume 12, issue 5
Research article
11 Mar 2015
Research article |  | 11 Mar 2015

Thermal-based modeling of coupled carbon, water, and energy fluxes using nominal light use efficiencies constrained by leaf chlorophyll observations

M. A. Schull, M. C. Anderson, R. Houborg, A. Gitelson, and W. P. Kustas

Abstract. Recent studies have shown that estimates of leaf chlorophyll content (Chl), defined as the combined mass of chlorophyll a and chlorophyll b per unit leaf area, can be useful for constraining estimates of canopy light use efficiency (LUE). Canopy LUE describes the amount of carbon assimilated by a vegetative canopy for a given amount of absorbed photosynthetically active radiation (APAR) and is a key parameter for modeling land-surface carbon fluxes. A carbon-enabled version of the remote-sensing-based two-source energy balance (TSEB) model simulates coupled canopy transpiration and carbon assimilation using an analytical sub-model of canopy resistance constrained by inputs of nominal LUE (βn), which is modulated within the model in response to varying conditions in light, humidity, ambient CO2 concentration, and temperature. Soil moisture constraints on water and carbon exchange are conveyed to the TSEB-LUE indirectly through thermal infrared measurements of land-surface temperature. We investigate the capability of using Chl estimates for capturing seasonal trends in the canopy βn from in situ measurements of Chl acquired in irrigated and rain-fed fields of soybean and maize near Mead, Nebraska. The results show that field-measured Chl is nonlinearly related to βn, with variability primarily related to phenological changes during early growth and senescence. Utilizing seasonally varying βn inputs based on an empirical relationship with in situ measured Chl resulted in improvements in carbon flux estimates from the TSEB model, while adjusting the partitioning of total water loss between plant transpiration and soil evaporation. The observed Chl–βn relationship provides a functional mechanism for integrating remotely sensed Chl into the TSEB model, with the potential for improved mapping of coupled carbon, water, and energy fluxes across vegetated landscapes.

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