GPP Estimation of a Grassland Ecosystem Based on Photosynthesis-Hydrology Coordination Optimization

Accurate estimation of gross primary production (GPP, ecosystem level photosynthesis) is critical for monitoring terrestrial ecosystems. However, most of the current models used for GPP estimation are with many unknown parameters and rarely include the effects of soil water stress due to the covariation of soil moisture and air humidity. In addition, grasslands, as the most widely distributed ecosystems in the world, have simple ecosystem structure and are easily affected by soil drought. Therefore, in this paper, we applied photosynthesis-hydrology coordination optimization theory and soil water potential based on soil moisture effect to develop a combined model (PH model) for GPP estimation of grassland ecosystems and used the US-Var grassland ecosystem, one of the FLUXNET sites from January to July 2004 (the driest period in recent years) as an example to validate the model. The results show that the model can effectively track the measured GPP during soil drought period and is better than the result from another commonly used photosynthesis coordination model (Pmodel) which does not consider the effect of soil drought. Further, we can infer the vegetation photosynthetic capacity parameters including the maximum carboxylation capacity (V cmax) and the maximum electron-transport capacity (Jmax) under the effect of soil drought. The result also shows that if soil drought is not considered, the photosynthetic capacity parameters of vegetation will be overestimated. These results provide evidence for the application of photosynthesis-hydrology coordination theory in the assessment of ecosystem carbon cycle under the intensified climate changes.