Calibrating a coupled SVAT-vegetation growth model with remotely sensed reflectance and surface temperature - A case study for the HAPEX-Sahel grassland sites

Models simulating the seasonal growth of vegetation have been recently coup led to soil-vegetation-atmosphere transfer schemes (SVATS). Such coupled ve getation-SVATS models (V-S) account for changes of the vegetation leaf area index (LAI) over time. One problem faced by V-S models is the high number of parameters that are required to simulate different sites or large areas. Therefore, efficient calibration procedures are needed. This study describ es an attempt to calibrate a V-S model with satellite [Advanced Very High R esolution Radiometer (AVHRR)] data in the shortwave and longwave domains. A V-S model is described using ground data collected over three semiarid gra ssland sites during the Hydrological Atmospheric Pilot Experiment (HAPEX)-S ahel experiment. The effect of calibrating model parameters with time serie s of normalized difference vegetation index (NDVI) and thermal infrared (TI R) data is assessed by examining the simulated latent heat flux (LE) and LA I for a suite of calibration experiments. A sensitivity analysis showed tha t the parameters related to plant growth vigor and to soil evaporative resi stance were the best candidates for calibration. The NDVI and TIR time seri es were used to calibrate these parameters, both independently and simultan eously, to assess their synergy. Ground-based, airborne, and satellite sens or (AVHRR) data were successively investigated. Both airborne and AVHRR NDV I data could be used to constrain the vegetation growth vigor. These calibr ations significantly improved the simulation of the LAI and LE (rmse decrea sed by 21% for LE), and the site-to-site variability was greatly enhanced. The soil resistance could also be calibrated with ground-based TIR data, bu t the effect on the simulated variables was small. Although both NDVI and g round-based TIR data were suitable to constrain the V-S model, the synergy between the two wavelengths was not clearly established. Last, satellite TI R data from the AVHRR proved unsuitable for model calibration. Indeed, the AVHRR surface temperature values were systematically lower than both ground -based data and model outputs. The authors conclude that the calibration of a vegetation-SVAT model with shortwave AVHRR time series can be used to sc ale the energy and water fluxes up to the regional scale.