Large-scale simulation of wheat yields in a semi-arid environment using a crop-growth model

The ability to predict wheat yields from large-scale weather variables has benefits throughout the semi-arid regions of the world. In spite of the ava ilability of numerous crop-growth models, there has been little concerted e ffort to analyse yields regularly at spatial scales that are relevant to ag ronomic decision makers. As a result many current crop-growth models are re search tools only. A large-scale wheat yield assessment procedure, based on the CERES Wheat model, has been developed for the semi-arid climate of Sas katchewan. It is suitable for simulating yields at the crop-district level, an area of about 2 million hectares containing several hundred farms havin g different soils, climates and management practices. Simulations of spring wheat growth, using this procedure, have revealed two critical periods (ve getative and ear growth) when lack of moisture has the greatest impact on g rain yields. Knowledge of these times could be useful in devising early war ning programmes for drought amelioration, combined with reliable long-term climate forecasts. Decisions made during these critical periods would affec t farm management, marketing strategy and planning for the next growing sea son. (C) 1999 Elsevier Science Ltd. All rights reserved.