ICARDA annual report 2004

Project 3.4.
Agroecological Characterization for
Agricultural Research, Crop Management, and
Development Planning
R
emote sensing and geographical information systems
(GIS) are powerful and flexible tools that ICARDA is using
to integrate multi-thematic data into new applications to
support its research. In 2004, ICARDA scientists developed an
index-based method to map ‘agricultural resource poverty’ and
the ‘agricultural resource endowment’ of different areas. They
also developed two new mapping approaches: a national
approach to address the needs of agricultural planners and decision-makers,
and a participatory approach to capture the local
agroecological knowledge of farmers and land users.
Mapping agricultural
resource poverty and
resource endowments in
CWANA
CWANA probably has the highest
proportion of marginal agricultural
land in the world, and thus the
highest level of ‘agricultural
resource poverty.’ This is mainly
due to an unfavorable agricultural
climate, complex topography, and a
lack of water and soil resources.
Climatic factors such as temperature,
which determines when crops
can be grown, most limit agriculture
in the region. Water availability is
also a major constraint, though in
some cases this can be alleviated
using irrigation. The topography of
CWANA’s many mountainous
areas is also a constraint, as rivers,
valleys, steep slopes, and poor
accessibility all greatly reduce the
available area of good-quality farmland.
Finally, the region’s soils suffer
from such problems as salinity,
sodicity, shallowness, high levels of
stoniness, and a very coarse texture,
all of which are either impossible or
too expensive to correct.
Constraints such as these probably
play a key role in human poverty.
However, the links between
these factors and poverty have not
been studied in enough depth, particularly
in CWANA. Agricultural
resource poverty, therefore, needs
to be quantified. However, this is
difficult, because the biophysical
factors involved are complex and
interact with each other.
ICARDA researchers developed
an index-based method of quantifying
resource poverty that can be
used to produce an agricultural-
Theme 3
resource-poverty index (ARPI).
This simple method considers all
relevant biophysical factors, and
allows different locations to be
compared consistently. It incorporates
an ‘audit trail,’ to assess the
contributions that individual environmental
factors make to agricultural
resource poverty, and is scaleindependent
and can be applied
using currently available datasets.
The model has a broad scope, but
does not take into account land and
water resource degradation caused
by poor management.
Researchers determine an ARPI
value by considering three separate
indices, each of which represents
one component of resource poverty
(Fig. 23):
• Climatic and water resource
poverty (CWRPI), derived from
data such as temperature, rainfall,
and plant productivity
• Soil resource poverty (SRPI),
derived from the FAO Soil Map
of the World
• Topographic resource poverty
(TRPI), derived from the U.S.
Geological Survey’s GTOPO30
Global Digital Elevation Model
Each index has a value within
the range 0-100; the highest of these
three values is taken to be the value
of the ARPI. So, the ARPI also
ranges between 0 and 100.
Fig. 23. Main
steps involved
in developing
the Agricultural
Resource
Endowment
Index.
ICARDA Annual Report 2004
55