Assessing MODIS carbon and water fluxes in grasslands and shrublands in semiarid regions using eddy covariance tower data

Abstract

ABSTRACT Gross primary productivity (GPP) and evapotranspiration (ET) are two important fluxes between the terrestrial ecosystems and the atmosphere. Remote sensing data-driven models have been successfully used to estimate carbon and water fluxes in various ecosystems, but the models are still underperforming in dryland. In this study, the agreement between the Moderate Resolution Imaging Spectroradiometer (MODIS) products, MODIS data-driven models, and the eddy covariance (EC) tower observation data were tested for two different ecosystem sites in arid regions in Xinjiang, China. The results convincingly indicated that the MODIS products can successfully capture the temporal GPP and ET variables for grasslands and shrublands, but these results have large biases. The MODIS GPP products certified contributed 88% of the EC observed GPP for the grassland but 16% for the shrubland. The temperature and greenness (TG) model clearly showed favourable correspondence with tower GPP observed in arid regions, with the coefficient of determination (R 2) of 0.91 and root mean square error (RMSE) of 17.65 g C m−2 16 days−1. The ET performance was evaluated at two sites, yielding R 2 values of 0.77 and 0.34 for the grassland and shrubland, respectively. Our study showed that the source of uncertainties comes from the remotely sensed data input in GPP and ET algorithms.