Comparison of satellite-based models for estimating gross primary productivity in agroecosystems

Satellite-based gross primary productivity(GPP) models have been widely used for simulating carbon exchanges of terrestrial ecosystems. However, the performances of various GPP models in agroecosystems have been rarely explored. In this study, we calibrated the model parameters and compared the performances of seven light use efficiency (LUE-GPP) models and five vegetation-index (VI-GPP) models for simulating daily GPP of agro-ecosystems over 106 crop growing seasons, and examined the effects of model structure on model performance. The simulations were carried out based on 19 eddy covariance (EC) sites from the global flux network and vegetation indices obtained from MoDIS. The calibrated potential LUE (epsilon(max)) for C-4 crop (summer maize, 2.59 +/- 0.94 g C MJ(-1)) was higher than that for C-3 crops (1.42 +/- 0.58 g C MJ(-)(1)) in any LUE-GPP models. The performances of models differed across the crops. Generally, all models performed better for C-3 crops than C-4 crops, and for winter crops (winter wheat Triticion aestivum L, rape-Bra.ssira napes L, and winter barley-llardeurn vulgare L) than summer crops (summer make-Zea mays L, potato :Solarium tuberosum L, rice-Otyza saliva L. and soybean-Glycine max (L.) Merr.). Cloudiness index-LUE (CI-LUE) model outperformed the other LUE-GPP models, and vegetation index (VEI) model outperformed the other VI-GPP models. LUE-GPP models demonstrated better performance than VI-GPP models due to the inclusion of water stress (W-s) and temperature stress (T-s). A comparison of the model structures showed that models only considering the effects of W-s produced smaller errors than those only considering the effects of T-s in simulating GPP. W-s algorithms generated the larger variations in LUE-GPP models compared to those of T-s especially during the drought period. All models obtained higher R-2 and smaller errors using the minimum method (Min (T-s, W-s)) than using the multiplication method (T-s x W-s) to integrate the effects of T-s and W-s on GPP, which suggested that the minimum method was better than the multiplication method to integrate T-s and W, on LUE. These results showed that satellite-based models with calibrated crop-specific parameters have the potential to serve as the basis for estimation of agroecosystem GPP, and can provide direction for future model structure optimization.

Automated summary

Satellite-based Gross Primary Productivity (GPP) models are widely used for carbon exchange simulation of terrestrial ecosystems, but their performance in agro-ecosystems is not well-explored. This study compared the performances of seven LUE-GPP models and five VI-GPP models for simulating daily GPP of agro-ecosystems, finding that the CI-LUE model outperformed the others.