Community Research and Development Information Service - CORDIS

Agrometeorological models for crop yield forecasting

Agrometeorological models based as a comprehensive database containing information about weather, soils, topography and crop parameters have been developed to improve assessments of crop state and yield forecasts at the level of the European Community member states. A prototype model is now installed and being used to produce preoperational outputs every month. The geographical data which are the input to the agrometeorological models can be divided into 5 main categories: weather, soils, crop parameters, topography and historical crop statistics. In some cases the agrometeorological models can be improved by the inclusion of data which are not readily available. Parameters such as potential evapotranspiration, solar radiation and soil water balance are not normally available in meteorological bulletins. Work has therefore been undertaken to develop algorithms to derive these data from information which is available. The agrometeorological models are designed to produce results on a regular spatial grid, initially containing cells of 50 kms by 50 kms. The input data, however, are not received on the basis of this grid. The meteorolgical data, for instance, are collected from stations which are irregularly distributed across Europe. Work has been undertaken to develop methodologies to interpolate weather measurements from the stations to the grid squares. The present algorithm which interpolates basic data such as temperature and wind speeds is being validated and refined. The algorithms developed for crop modelling have been implemented in a prototype system. This system guides the user through the processing chain and presents the results in the form of maps and tabular reports. The database developed for the main agrometeorological model has also been used as the basis of an exercise to develop an algorithm for estimation of long term mean grape sugar content.

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Joint Research Centre, Ispra
21020 Ispra
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