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

Abstract

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 availability of numerous crop-growth models, there has been little concerted effort to analyse yields regularly at spatial scales that are relevant to agronomic decision makers. As a result many current crop-growth models are research tools only. A large-scale wheat yield assessment procedure, based on the CERES Wheat model, has been developed for the semi-arid climate of Saskatchewan. It is suitable for simulating yields at the crop-district level, an area of about 2 million hectares containing several hundred farms having different soils, climates and management practices. Simulations of spring wheat growth, using this procedure, have revealed two critical periods (vegetative and ear growth) when lack of moisture has the greatest impact on grain yields. Knowledge of these times could be useful in devising early warning programmes for drought amelioration, combined with reliable long-term climate forecasts. Decisions made during these critical periods would affect farm management, marketing strategy and planning for the next growing season. ©