HR: 1340h
AN: B33D-1069    [Abstracts]
TI: Uncertainty in water limited ecosystem carbon fluxes estimated with optical and thermal spaceborne sensors
AU: * Verstraeten, W W
EM: willem.verstraeten@vito.be
AF: VITO, Boeretang 200, Mol, Fla B-2400 Belgium
AU: * Verstraeten, W W
EM: willem.verstraeten@vito.be
AF: Katholieke Universiteit Leuven, Vital Decosterstraat 102, Leuven, Fla B-3000 Belgium
AU: Veroustraete, F
EM: frank.veroustraete@vito.be
AF: VITO, Boeretang 200, Mol, Fla B-2400 Belgium
AU: Feyen, J
EM: jan.feyen@biw.kuleuven.be
AF: Katholieke Universiteit Leuven, Vital Decosterstraat 102, Leuven, Fla B-3000 Belgium
AB: Global carbon budget studies are, currently, still dominated by temperature analysis only because of the importance of this climatologic variable on photosynthesis and soil carbon dynamics. Yet, a strong coupling between the carbon and the hydrological cycle is observed. To take into account water limitation in carbon studies, water availability for vegetation must be estimated first. Hence, to asses water limited ecosystem carbon fluxes with optical and thermal sensor data, soil moisture and vegetation evaporation has to be estimated. Integration of the water cycle into ecosystem carbon modelling using remote sensing involves additional uncertainty in model results. The objective of this paper is the discussion of uncertainties in the retrieval of water limited Net Ecosystem Productivity (NEP), evaporative fraction (EF) and soil moisture content (SMC), obtained from optical and thermal coarse resolution NOAA/AVHRR and METEOSAT imagery. EF is calculated using the hydrological properties of a combined albedo - land surface temperature relationship, established with the Integral NOAA-imagery processing Chain (iNOAA-Chain; Verstraeten et al., 2005). SMC is derived from thermal inertia (TI), combining albedo and the difference of day and night land surface temperatures using the Integral METEOSAT-imagery processing Chain (iMETEOSAT-Chain; Verstraeten et al.). A soil moisture saturation index (SMSI) is calculated from TI and is filtered through a 1st order Markov model, converting surface values of SMC to soil profile values. Finally, EF and SMC are integrated into the Product Efficiency Model C-Fix (Veroustraete et al., 2002, 2004, Verstraeten et al.). Error propagation and Monte-Carlo based models (Generalised Likelihood Uncertainty Estimation, Beven and Binley, 1992) are applied respectively on the EF, SMC and NEP (sub-) models of European pixels for the growing season of 1997, to estimate uncertainty. We present uncertainty on EF, SMC and NEP time series at different EUROFLUX sites. From preliminary results typical absolute errors of 0.154+/-0.021 cm3/cm3 for SMC values, of 0.50+/-0.13 for EF values and of 4.21+/-3.00 gC/m2/d for NEP values are obtained.
DE: 0466 Modeling
DE: 0480 Remote sensing
DE: 1878 Water/energy interactions (0495)
DE: 4806 Carbon cycling (0428)
SC: Biogeosciences [B]
MN: Fall Meeting 2005