Geoscience Reference
In-Depth Information
4500
4000
3500
3000
2500
Simulated (kg/ha)
Observed (kg/ha)
2000
1500
1000
500
0
5th July
15th July
25th July
FIGURe 3.5
CERES-Rice model for yield prediction in kg/ha
at different dates of transplanting.
•
Integrating across disciplines
•
Assisting in genetic improvement
•
Evaluate optimum genetic traits for specific
environment
•
Evaluate cultivar stability under long-term weather
policy
manage ment
Policy management is one very useful application of crop simu-
lation models. The issues range from global (impacts of climate
change on crops) to field-level (effect of crop rotation on soil
quality). During 1997, it was shown that in Burkina Faso, crop
simulation modelling using satellite and ground-based data
could estimate millet production for an early warning of fam-
ine which can allow policy makers the time they need to take
appropriate steps to ameliorate the effects of global food short-
age on vulnerable urban and rural populations. In Australia,
it was observed that during November-December when the
SOI (Southern Oscillation Index) phase is positive, there is an
80% chance of exceeding average district yields. Conversely, in
years when the November-December SOI phase is either nega-
tive or rapidly falling, there is only a 5% chance of exceeding
average district yields, but 95% chance of below average yields.
This information allows the industry to adjust strategically for
the expected volume of production. Crop models can be used to
understand the effects of climate change such as consequences
of ele vated CO
2
and changes in temperature and rainfall on
