Abstract
Crop simulation models are used widely to predict crop growth and development in studies of the impact of climatic change. 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 in order 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. The system can perform real-time simulations of crop growth and assess crop productivity and its associated risk before harvest using recorded meteorological data from a current season supplemented by stochastically generated meteorological data. The considerable flexibility used to construct climatic scenarios, on the basis of the weather generator, makes AFRCWHEAT 3S a useful tool in studies of the impact of climatic change on wheat crops. Sensitivity analyses to changes in the variability of temperature and precipitation, as compared with changes in their mean values, were made for location in the UK for winter wheat. Results indicated that changes in climatic variability can have a more profound effect on yield and its associated risk than did changes in mean values.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call