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

Abstract

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 carbonenabled version of the remote-sensing-based two-source energy balance (TSEB) model simulates coupled canopy transpiration and carbon assimilation using an analytical submodel of canopy resistance constrained by inputs of nominal LUE (β n ), which is modulated within the model in response to varying conditions in light, humidity, ambient CO 2 concentration, and temperature. Soil moisture constraints on water and carbon exchange are conveyed to the TSEB-LUE indirectly through thermal infrared measurements of landsurface temperature. We investigate the capability of using Chl estimates for capturing seasonal trends in the canopy β n 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 β n , with variability primarily related to phenological changes during early growth and senescence. Utilizing seasonally varying β n 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-β n 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.

Reviews and Syntheses: optical sampling of the flux tower footprint

“…Alternatively, efficiency (ε) can be addressed using meteorological data (temperature and vapor pressure deficit) according to Eq. (3), or can be addressed with thermal remote sensing and modeling methods (Anderson et al, 2008;Schull et al, 2015). To most directly compare with eddy covariance, which measures NEE (analogous to NPP), additional modeling, or partitioning into gross ecosystem production (GEP, analogous to gross primary production, GPP) and respiration (R), is needed.…”

“…Recent findings of a functional link between PRI, carotenoid biochemistry, and vegetation isoprenoid emission (Peñuelas et al, 2013) indicate that PRI and carotenoid biochemistry can offer new insights into the controls on other trace gas fluxes in addition to CO 2 . Other concurrent sampling methods, including thermal methods that provide independent assessment of chronic stresses, can add even greater insight into flux controls by integrating evapotranspiration and energy balance with the LUE approach (Anderson et al, 2008;Schull et al, 2015). Consequently, there is ample opportunity for further exploration and clarification of diurnal and seasonal flux controls by integrating indices such as NDVI and PRI with other sampling methods (e.g., irradiance, fluorescence, and thermal measurements), and flux towers properly instrumented with optical sensors offer ideal opportunities for further investigation of this topic.…”

“…Better integration of optical with structural (e.g., LIDAR) measurements, particularly using canopy radiative transfer models (e.g., van der Tol et al, 2009), would provide further insight into the structural vs. physiological controls on carbon flux, and could help explain emergent proper-ties. Integration of thermal sampling methods could help integrate energy balance and water vapor fluxes with the LUE approach (Anderson et al, 2008;Schull et al, 2015).…”

Productivity, absorbed photosynthetically active radiation, and light use efficiency in crops: Implications for remote sensing of crop primary production

“…This figure highlights the difference in the efficiency of the use of radiation absorbed by irrigated and rainfed crops in the reproductive stage. To our knowledge such behavior of LUE green has not yet been conclusively demonstrated except for a brief discussion in Gitelson et al (2014). Further experimental work is needed to explore the possible reason for this result.…”

“…The uncertainties of such LAI green determination increase in the reproductive stage when leaf chlorophyll content/greenness decreases (Gitelson et al, 2014a). To make accurate comparison across sites and years, following Turner et al (2003) and Schull et al (2014), in addition to whole growing season change (Figure 10), GPP and aPAR data for the period June 1 to August 30 were used. The temporal constraint criteria served to eliminate days early in the growing season (green LAI < 2) when uncertainties of aPAR and GPP were greatest.…”