Abstract
We investigate in this study (i) a redefinition of crop variety zonations at a spatial scale of 10x10 km, and (ii) the influence of recalibrated crop parameters on regional yield forecasting of winter wheat and grain maize in western Europe. The baseline zonation and initial crop parameter set was derived from the operational European crop growth monitoring system (CGMS) which involves the agrometeorological model WOFOST. Air temperature data from 325 weather stations over the 1992-2007 period were used to define new zonations in a 300 x 300 km test site. Two parameters which influenced mostly the phenological development stages (i.e. TSUM1 and TSUM2, the effective air temperature sums from emergence to anthesis, and from anthesis to maturity, respectively) were chosen and calibrated. The CGMS was finally run based on these new recalibrated parameters and simulated crop status indicators were compared with official statistics over the 2000-2007 period. Our results showed that the days of anthesis and maturity were simulated with coefficients of determination (R2) ranging from 0.22 to 0.87 for both crops over the study site. A qualitative assessment of maximum leaf area index and harvest index also revealed a more consistent spatial pattern than the initial zonation in the simulation results. Finally, recalibrated TSUM1 and TSUM2 led to improved relationships between official yield and simulated crop indicators (significant R2 in 17 out of 28 and in 14 out of 59 NUTS3 regions with respect to the best predictor for grain maize and winter wheat, respectively).
Highlights
And accurate information on crop yield and production have led to the development of several forecasting systems applied at various temporal and spatial scales
We investigate in this study (i) a redefinition of crop variety zonations at a spatial scale of 10x10 km, and (ii) the influence of recalibrated crop parameters on regional yield forecasting of winter wheat and grain maize in western Europe
The MCYFS is based on the simulation of the crop growth monitoring system (CGMS), and for crops it allows regional application of the WOFOST (World Food Study, van Diepen, Wolf, & van Keulen, 1989; van Ittersum et al, 2003) model by providing a framework which handles model inputs, model outputs, aggregation to statistical regions, and yield forecasting at these different administrative levels
Summary
And accurate information on crop yield and production have led to the development of several forecasting systems applied at various temporal and spatial scales. The MCYFS is based on the simulation of the crop growth monitoring system (CGMS), and for crops it allows regional application of the WOFOST (World Food Study, van Diepen, Wolf, & van Keulen, 1989; van Ittersum et al, 2003) model by providing a framework which handles model inputs (weather, soil, and crop parameters), model outputs (namely crop indicators such as total biomass, grain yield and leaf area index), aggregation to statistical regions, and yield forecasting at these different administrative levels The performance of such crop growth model in yield forecasting depends both on the model’s ability to reproduce the effects of environmental conditions and crop management practices, and on a proper aggregation of simulation results for individual land units towards higher aggregation levels. Spatial aggregation of inputs prior running the model may give different results than aggregating model outputs
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