Geoscience Reference
In-Depth Information
Field experimentation on a range of scales
has been attempted to try and deal with some
of the above spatial and temporal issues. In the
1990s the EU-funded experimental field studies
IBERLIM and MEDALUS (Case Study 5.3)
generated field data that were used to generate
computer simulation models (Kirkby et al. 1998)
of surface runoff, vegetation and erosion and
their interplay through space and time on both a
hillslope (MEDALUS model) and large, up to
5000 km 2 , catchment scale (MEDRUSH model).
These were calibrated with the collected field
data and are being used to explore future trends
under different scenarios. All modelling, how-
ever, is fraught with difficulties of scale. Global
climate models (GCMs) use cells of
the year 2100) point towards raised temperatures,
lower precipitation and lower soil moisture in
general, for the zone 30°N-30°S of the Equator.
This zone contains many of the world's arid
environments (Fig. 5.2). In areas such as the
Atacama Desert of South America impacts of
global climate change on the duration, magni-
tude and frequency of El Niño and La Niña need
to be understood, as these phenomena are signi-
ficant for rainfall generation in such regions.
Dryland landscapes and their associated
vegetation systems, which help control rates of
landscape change, are naturally dynamic and
have a degree of resilience to environmental
change. These systems thus have some natural
resistance to human intrusion. With a burgeon-
ing global population, however, our intervention
with the arid environment will only increase as
demand for resources increases, particularly
if, as predicted by GCMs, the spatial extent
of drylands expands/intensifies in response to
factors such as global warming. Thus there is
a need to address the issues of sustainability in
such environments in order to avoid currently
localized impacts becoming more global. This
may require embracing remote sensing tech-
nology and integrating it with field studies to
monitor dryland environments and the nature
of changes within them. These data, together
with longer term Quaternary data, can be used
to try and better understand the complexities
of dryland environments and their response to
environmental change. If, however, this know-
ledge is to be successfully implemented in the
sustainable management of dryland systems
we need to ensure that scientists communicate
with the decision makers more effectively
(Thomas 1997c).
0.5° latitude
and longitude, and yet previous work has shown
that detailed knowledge is needed of a wide
range of variables, much smaller than this cell
size (such as rocky surface conditions and cover,
Yair 1994), to have any hope of accurately pre-
dicting the magnitude and size of change.
Debates rage on prediction of future climate
change and whether global warming or cool-
ing will prevail. Predictions from the generated
GCMs vary widely. Integration of the data
from three of the main GCMs for doubled
atmospheric CO 2 levels indicates that southern
European drylands (bordering the Mediterranean)
will have increases in summer temperature of
+
<
6°C in
the winter, with associated overall significant
decreases in precipitation and overall avail-
able soil moisture (Williams & Balling 1995).
The Hadley Centre for Climate Prediction and
Research (UK) provides a summary of some of the
various types of models available through links
on www.metoffice.com. These predictions (to
4 to
+
6°C in the summer, and
+
2 to
+
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