Showing papers by "Allard de Wit published in 2013"
TL;DR: In this paper, the output of regional climate models (RCMs) was bias corrected and applied within the crop simulation model WOrld FOod STudies to simulate potential and water limited yields of three divergent crops: winter wheat, maize and sugar beet.
Abstract: Excessive summer drying and reduced growing season length are expected to reduce European crop yields in future. This may be partly compensated by adapted crop management, increased CO2 concentration and technological development. For food security, changes in regional to continental crop yield variability may be more important than changes in mean yields. The assessment of changes in regional and larger scale crop variability requires high resolution and spatially consistent future weather, matching a specific climate scenario. Such data could be derived from regional climate models (RCMs), which provide changes in weather patterns. In general, RCM output is heavily biased with respect to observations. Due to the strong nonlinear relation between meteorological input and crop yields, the application of this biased output may result in large biases in the simulated crop yield changes. The use of RCM output only makes sense after sufficient bias correction. This study explores how RCM output can be bias corrected for the assessment of changes in European and subregional scale crop yield variability due to climate change. For this, output of the RCM RACMO of the Royal Netherlands Meteorological Institute was bias corrected and applied within the crop simulation model WOrld FOod STudies to simulate potential and water limited yields of three divergent crops: winter wheat, maize and sugar beets. The bias correction appeared necessary to successfully reproduce the mean yields as simulated with observational data. It also substantially improved the year-to-year variability of seasonal precipitation and radiation within RACMO, but some bias in the interannual variability remained. This is caused by the fact that the applied correction focuses on mean and daily variability. The interannual variability of growing season length, and as a consequence the potential yields too, appeared even deteriorated. Projected decrease in mean crop yields is well in line with earlier studies. No significant change in crop yield variability was found. Yet, only one RCM is analysed in this study, and it is recommended to extend this study with more climate models and a slightly adjusted bias correction taking into account the variability of larger time scales as well.
18 citations
TL;DR: In this article, the authors applied the Carnegie-Ames-Stanford Approach CASA agroecosystem model to obtain net primary production, dry matter productivity, and crop yield using only LSA-SAF products.
Abstract: Finally, the use of the ET product is also explored by integrating it in a simpler modelling approach based on light-use efficiency. The Carnegie–Ames–Stanford Approach CASA agroecosystem model was therefore applied to obtain net primary production, dry matter productivity, and crop yield using only LSA-SAF products. The values of yield were compared with those obtained using CGMS, and the dry matter productivity values with those produced at the Flemish Institute for Technological Research VITO. Results showed the potential of using this simplified remote-sensing method for crop monitoring.
12 citations
08 Oct 2013
TL;DR: In this article, the authors describe the efforts that were carried out for adapting the European Crop Growth Monitoring System to Moroccan conditions for crop monitoring and regional yield forecasting, and demonstrate that the correlations between CGMS output and regional reported yields can be strongly improved by relatively simple changes to the parameterization of the crop model and a different strategy for the initialization of the soil water balance.
Abstract: Morocco has an agricultural production system for cereals which is dominated by rainfed, low yielding cereal production which is highly vulnerable to fluctuations in rainfall. Crop yield forecasting systems could play a significant role to reduce the vulnerability of the Moroccan agriculture to weather risks in the framework of a food security strategy. This paper describes the efforts that were carried out for adapting the European Crop Growth Monitoring System to Moroccan conditions for crop monitoring and regional yield forecasting. Results demonstrate that the correlations between CGMS output and regional reported yields can be strongly improved by relatively simple changes to the parameterization of the crop model and a different strategy for the initialization of the soil water balance.
4 citations