CLIMATIC VARIABILITY AND THE MODELING OF CROP YIELDS

Crop simulation models are used widely to predict crop growth and development in studies of the impact of climatic change. An important problem is the uncertainty inherent in the construction of the future weather scenarios used as inputs to models. In seeking to couple meteorological information to crop-climate models it must be remembered that many interactions between crops and weather are non-linear. Non-linearity of response means it is necessary to preserve the variability of weather sequences to estimate the effect of climate on agricultural production and to assess agricultural risk. To date, only changes in average weather parameters derived from general circulation models (GCMs) and then applied to historical data have been used to construct climatic change scenarios and in only a few studies were changes in climatic variability incorporated. Accordingly, a computer system, AFRCWHEAT 3S, was designed to couple the simulation crop model for wheat, AFRCWHEAT2, with a stochastic weather generator based on the series approach. AFRCWHEAT 3S provides flexible construction of climatic scenarios and allows changes not only in mean values but also in the variance or type of distribution for a wide variety of weather parameters. Analyses of sensitivity to changes in the variability of temperature and precipitation, as compared with changes in their mean values, were made for locations in the UK and France for winter wheat. Results indicated that changes in climatic variability can have a more profound effect on yield and its associated risk than changes in mean climate.