Estimation of the Components of the Carbon and Water Budgets for Winter Wheat by Combining High Resolution Remote Sensing Data with a Crop Model
Friday, 19 December 2014: 5:15 PM
Croplands occupy more than one third of Earth’s terrestrial surface contributing to climate change and also being impacted by those changes, since their production is conditioned by climatic conditions and water resources. It is thus essential to quantify and analyze the production and the main components of the carbon and water cycles for crop ecosystems. We propose here a regional modeling approach that combines: high spatial and temporal resolutions (HSTR) optical remote sensing data, a simple crop model and an extensive set of in-situ measurements for model’s calibration and validation. The model, named SAFYE-CO2 (Simple Algorithm for Fluxes and Yield Estimates), is a daily time step model based on Monteith’s light-use efficiency theory and coupled with a water budget module (FAO-56 method). SAFYE-CO2 estimates components of the carbon budget (gross primary production (GPP), ecosystem respiration (Reco), net ecosystem exchange (NEE), …) and of the crop water cycle (evaporation, transpiration, evapotranspiration (ETR) and soil water content) and also time courses of dry aboveground biomass and yield by assimilating Green Area Index (GAI) data obtained from HSTR satellite observations. For this work, we used a unique set of Formosat-2 and SPOT images acquired from 2006 to 2011 in southwest France. Crop and soil model parameters were set using both in-situ measurements and values found in the literature. Phenological parameters were calibrated by the GAI assimilation. The results indicate that the model correctly reproduces winter wheat biomass and yield production (relative error about 25%) for years with contrasted climatic conditions. The estimated net carbon flux components were overall in agreement with the flux measurements, presenting good correlations (R² about 0.9 for GPP, 0.77 for Reco and 0.84 for NEE). Regarding the ETR, a good correlation (R2 about 0.73) and satisfactory errors (RMSE about 0.47 mm.d-1) were found. Carbon and water budgets as well as some water use efficiency (WUE) indices were computed, allowing to evaluate the crop ecosystems in terms of environmental and agronomical aspects. Still, the performances of this method could be improved by considering weeds or re-growths events after harvest. This approach could be extended to a global scale thanks to the future Sentinel-2 products.