R. Gommes, Senior Agrometeorologist
M. Bernardi, Agrometeorologist
and F. Petrassi, Statistical Clerk
Environment and Natural Resources Service (SDRN)
FAO Research, Extension and Training Division
CROP FORECASTING is the art of predicting crop yields (tons/ha) and
production before the harvest actually takes place, typically a couple
of months in advance. Several techniques can be used. What is described
here is the approach used by FAO in national food security systems.
Crop forecasting relies on computer programmes that describe the
plant-environment interactions in quantitative terms. Such programmes
are called "models", and they attempt to simulate
plant-weather-soil interactions. They need, therefore, information
and data on the most important factors that affect crop yields - the
model inputs. After passing "through" the model, the
inputs are converted to a number of outputs, such as maps of
crop conditions and yields.
Violent weather factors - cyclones, floods and storms - catch the
attention of the public and usually receive wide media coverage. Due
to their rare occurrence and unpredictable timing, they are usually
extremely difficult to model. It should be stressed, however, that
far more agricultural production is lost to "chronic"
problems, such as local droughts, and recurrent pest attacks, than to
the violent ones.
Over the last 20 years, FAO has developed a crop forecasting "philosophy"
through a number of national projects to establish national early warning
systems. The FAO approach to crop forecasting philosophy is characterized
by the following:
- Integration of ground-based agrometeorological information
with remotely-sensed (satellite) information, both at the data and at the
product, or analysis, level
- A modular approach, i.e. crop forecasting tools that are
largely independent but can be combined, or "chained" as
required by local conditions. The modularity is an essential ingredient
of the sustainability of a national crop forecasting system as it
facilitates maintenance, training and upgrading of forecasting systems.