Estimating regional winter wheat yield with WOFOST through the assimilation of green area index retrieved from MODIS observations

Abstract

Within this paper we describe and test a methodology to optimize winter-wheat green area index (GAI) simulated by the WOFOST crop model using MODIS estimates of GAI over the Walloon region in Belgium. Detailed crop type maps over the period 2000-2009 were used to derive time-series of crop-specific GAI by selecting only those 250m MODIS pixels that have at least 75% purity for the target crop. Two important model parameters where optimized by minimizing the difference between simulated and observed GAI for each individual pixel and year. The resulting year-specific joint parameter distributions were used to run an ensemble of crop simulations where the ensemble was initialized by sampling from the joint distribution of the corresponding year. The semi-variograms of the retrieved parameters demonstrate that the spatial patterns are consistent with agricultural practices, while seasonal characteristics of weather patterns in Wallonia can, at least partially, explain the temporal variability in the retrieved parameter distributions. Finally, the average ensemble crop simulation results were aggregated to the level of provinces and regions. A validation with EUROSTAT reported yields over the period 2000—2009 demonstrates that the assimilation of MODIS GAI leads to an improved relationship between simulation results and reported yields at regional level.