Modeling gross primary production of paddy rice cropland through analyses of data from CO2 eddy flux tower sites and MODIS images

Abstract

Accurate information on the gross primary production (GPP) of paddy rice cropland is critical for assessing and monitoring rice growing conditions. The eddy co-variance technique was used to measure net ecosystem ex- change (NEE) of CO2 between paddy rice croplands and the atmosphere, and the resultant NEE data then partitioned into GPP (GPPEC) and ecosystem respiration. In this study, we first used the GPPEC data from four paddy rice flux tower sites in South Korea, Japan and the USA to evaluate the biophysical performance of three vegetation indices: Normalized Difference Vegetation Index (NDVI); Enhanced Vegetation Index (EVI), and Land Surface Water Index (LSWI) in terms of phenology (crop growing seasons) and GPPEC, which are derived from images taken by Moderate Resolution Imaging Spectroradiometer (MODIS) sensors. We also ran the Vegetation Photosynthesis Model (VPM), which is driven by EVI, LSWI, photosynthetically active radiation (PAR) and air temperature, to estimate GPP over multiple years at these four sites (GPPVPM). The 14 site-years of simulations show that the seasonal dynamics of GPPVPM successfully tracked the seasonal dynamics of GPPEC (R2 N 0.88 or higher). The cross-site comparison also shows that GPPVPM agreed reasonably well with the variations of GPPEC across both years and sites. The simulation results clearly demonstrate the potential of the VPM model and MODIS images for estimating GPP of paddy rice croplands in the monsoon climates of South Korea and Japan and the Mediterranean climate in California, USA. The application of VPM to regional simulations in the near future may provide crucial GPP data to support the studies of food security and cropland carbon cycle around the world.