Environmental Engineering Reference
In-Depth Information
under current economic conditions (Arthur
1988). A major problem in China would be an
increase in insect pests such as rice and corn
borers, rice winged fleas, army worms, aphids
and locusts. Dealing with these would raise pest
control costs by 1-5 per cent (NCGCC 1990).
Few simulations take such variables into account.
The model employed by Santer (1985) to predict
changes in European biomass potential included
no provision for such important elements as
insects, disease and additional fertilizers. Until
such unknowns can be estimated, the results of
this and similar simulations must be treated with
caution.
The most serious problem for agriculture is
the increasing dryness likely to accompany the
rising temperatures in many areas. Reduced
precipitation following changes in circulation
patterns, plus the increased rates of
evapotranspiration caused by higher
temperatures, would create severe moisture stress
for crops in many areas (Climate Institute 1988b).
Less precipitation and higher temperatures in the
farmlands of southern Ontario might reduce
yields sufficiently to cause losses of as much as
$100 million per year (Smit 1987). The areas
hardest hit would be the world's grain producing
areas, which would become drier than they are
now following the global warming (Kellogg
1987). Corn yields would be reduced in the mid-
western plains of the United States, and a major
increase in the frequency and severity of drought
would lead to more frequent crop failures in the
wheat growing areas to the north in Canada
(Williams
et al.
1988). The grain belt in Russia
and Ukraine, already unable to meet the needs
of these nations, would suffer as badly as its
North American equivalent (Kellogg 1987).
Such developments would disrupt the pattern
of the world's grain trade, which depends heavily
on the annual North American surplus. Food
supply problems would become serious in Russia,
and famine would strike many Third World
countries. In the early 1980s, the picture was not
considered completely hopeless, however, for
rainfall was expected to increase in some tropical
areas, and the combination of more rain, higher
temperatures and more efficient photosynthesis
would lead to increased rice yields of as much as
10 per cent (Gribbin 1981). Predictions for some
of the grain growing areas in Australia also
indicated increased precipitation and higher
temperatures (Kellogg 1987). However, a 1992
study by Martin Parry—a leading analyst of the
agricultural implications of global warming—
was much more pessimistic. Computer model
projections for the middle of the twenty-first
century indicated a decline of 15-20 per cent in
grain yields in Africa, tropical Latin America and
much of India and south-east Asia, leading to
major famine in these areas (Pearce 1992d). Such
variations are only to be expected. The many
elements which together determine the
distribution of natural and cultivated vegetation,
and the complex interrelationships involved, are
imperfectly understood. It is therefore very
difficult to depict them accurately in current
models. Coupled with the limited ability of most
global models to cope with regional scale
processes to which ecosystems respond, this
ensures that the ultimate changes in natural and
cultivated vegetation resulting from global
warming must remain speculative.
Most of the agricultural projections note the
importance of an adequate water supply if the
full benefits of global warming are to be
experienced. Beyond that, little work has been
done on the impact of an intensified greenhouse
effect on water resources. Canadian studies have
examined the implications of climate change for
future water resources in the Great Lakes—St
Lawrence River System (Sanderson 1987), and
in northern Quebec (Singh 1988). In Australia,
scientists using a high-resolution nested model
(see Chapter 2) have been able to simulate the
hydrology of the south-eastern part of the
continent more accurately than is possible with
existing global models. With a resolution about
ten times finer that that of the global models, the
nested model provides a better representation of
those regional factors—surface morphology, for
example—known to influence strongly the
distribution and intensity of precipitation and
run-off. The model has performed favourably in
