Gross primary production simulation in a coniferous forest using a daily gas exchange model with seasonal change of leaf physiological parameters derived from remote sensing data

Abstract

The importance of including the seasonal changes of canopy physiology in carbon balance simulation models was emphasized in earlier research. This paper proposes a new approach to combine the commonly available Normalized Difference Vegetation Index (NDVI) to derive the seasonal changes of canopy physiology with a modified daily step gas exchange model to simulate the gross primary production (GPP) in a coniferous forest stand. For validation, four years (1997–2000) of continuous time‐series data for GPP were derived using the observations of net ecosystem carbon dioxide exchange obtained with eddy covariance techniques. A variety of scenarios were designed to simulate the GPP with the daily model and the results (1) reaffirm the importance of including seasonal changes of canopy physiology in the carbon balance model; (2) demonstrate the feasibility of deriving the seasonal change information of canopy physiology from NDVI time‐series; (3) show the importance of the quality of NDVI time‐series. The results suggest that the daily model can be linked with remote sensing data, which provides information on the seasonal changes of canopy physiology, and can be an efficient tool for regional carbon balance simulation.