A Preliminary Simulation of the Potential for Sustainability
in Eritrea
Graduate Program in Environmental and Forest Biology, 301 Illick
Hall, SUNY- College of Environmental Science
and Forestry, Syracuse, NY 13210. E-mail:
REBEAL@syr.edu, REBEAL@ESF.edu
ABSTRACT
We are developing a spatial simulation model of the
population and agricultural production of Eritrea, a small country located in
East Africa. The simulation will be
used to test the sustainability of economic decisions in Eritrea. The model (ERISP4) has a yearly time step
that calculates annual human population growth, agricultural expansion,
fertilizer use, and agricultural production. The model has a series of
subroutines that contain simple algorithms that estimate yearly rainfall,
erosion, deforestation, energy use, and the costs of inputs for agricultural
production. ERISP4 utilizes several
digital raster maps of Eritrea representing elevation, soil type, rainfall, and
land use. Although the model is in its
early stages of development, initial simulation runs suggest that Eritrea may
exploit all available agricultural lands fully by the end of the decade and
that the country will require large food subsidies if its population continues
to grow rapidly. Moreover, the country
may be unable to afford the inputs required to ensure food “self-sufficiency” in the future.
INTRODUCTION
 |
Eritrea, a small country located in East Africa is that
continent’s newest nation. A
30-year war for independence has hindered development greatly. The country has required food subsidies 9 years
out of the first 10 years since independence. Eritrea currently has
a policy for developing agricultural self-sufficiency. The potential success of this policy is dependent on several biophysical
constraints including poor soils, low rainfall, high erosion rates,
and whether the 2.3% annual rate of population growth continues. Additionally, the sustainability of energy
production is unknown, although energy consumption has been increasing
10% annually. Simulation
models at the national scale allow one to develop and refine systems
analysis techniques, and provide tools, to integrate biophysical, economic
and social considerations into useful models for policy. A powerful
biophysical tool is the ability of simulation
models to incorporate a spatial component into economic and environmental
decision-making. The impact
of changes along the gradient of rain, temperature, soil type, elevation,
population, etc. can be used to evaluate the biophysical constraints
on large-scale economic policy decisions (Hall, 2000). |
The lowlands
of Eritrea are quite dry, while the highlands receive seasonal rains.
METHODS
We generated a FORTRAN model (ERISP4) that calculates
the population growth, agricultural production, energy use, deforestation,
and the estimated costs of agricultural production for a 100-year period in
Eritrea. Additionally, the model simulates
the expansion of agriculture in 2-dimensional space, based on the principles
of Best-Remaining-Land-Next proposed by Ricardo (1817). The model utilizes 2 digital maps of soil fertility
(IGADD, 1994) and a digital rainfall map (Woldu and Van Buskirk, 1997).
ERISP4 consists of 14 individual subunits. The model calculates annual
production for 5 types of crops and livestock, based on response to fertilizer,
soil, randomly-generated cloud cover and rainfall as well as the amount of
farmland for. The program has additional subunits that estimate
the annual costs of agricultural inputs, energy-use based on population and
affluence (10% annually), and deforestation (10% annually).
Several assumptions are made:
1. 5 Crops (representing 75% of annual historical production and
extrapolated to 100%) are simulated (Sorghum, Maize, Wheat, Pulses, and Barley
(also Livestock).
2. Human settlements take up no room.
3. Eritrean and Ethiopian crops have similar fertilizer response
curves (Ethiopian data is used to
estimate crop response to fertilizers).
4. There is a constant population
growth rate.
5. There are no outside food subsidies.
RESULTS
The simulation model predicts that Eritrea may be
nearing its biophysical carrying capacity.
The results show that:
1.Eritrea could run out of useable arable land by as early
as 2007 (Fig. 1).
2.Agricultural land most likely will be expanded in the
central highlands first, followed by the northern highlands and southern
deserts.
3.Crop production initially will rise as land and
fertilizer-use expand, with sorghum producing the highest yields (Fig. 2).
4.Crop production will decrease as the cumulative effect of
erosion increases (Fig. 2).
5.Stochastic rain variation will alter crop yields greatly
if irrigation is not expanded.
6.The population of Eritrea could reach 30 million by 2092
if current population growth rates continue (2.3%).
7. Three quarters of the population could require external
food subsidies by 2075 based on the caloric content of Eritrean crops (Fig. 3).
8.Yearly costs of foreign agriculture inputs could reach
close to 2 billion dollars annually by 2008 as extrapolated from FAO statistics
(Fig. 4).
9.Energy-use could increase by 8 orders of magnitude by 2092
as both population and affluence increase (Fig. 5). It is not clear where this energy would come from.
10.The model also predicts that Eritrea may loose all forest cover by 2030 (Fig. 6).
Fig.
1 Simulated expansion of agriculture
into lower quality regions in Eritrea over a 10 year period of intense
development. By 2007 all potential agricultural lands are utilized.
White=Eritrean border; Greens, Browns, Blues, Browns and Yellows=Agricultural
land expansion over time (1998 is actual data).
Fig. 2
Predicted yields for 5 crops and livestock in Eritrea over a 100 year
period. A stochastic weather function varies year-to-year crop yields.
The downward trend in the graph is due to an erosion function.
Fig.
3 The simulated population of Eritrea
over time (Blue). The
simulation uses the present growth rate of
2.3%. Population sustained
by simulated Eritrean crop production (pink).
Fig.
4 The simulated annual costs of
agricultural inputs in Eritrea. Costs
extrapolated from FAO statistics on Eritrean agriculture. Annual costs of agriculture may reach $1.8
billion by 2008.
Fig.
5 Simulated Energy-use in Eritrea over
Time. The rate
of energy consumption is based on extrapolated population growth and a 10%
annual increase in affluence.
Fig.
6 Forest Land Area in Eritrea over
Time. Deforestation
algorithm based on observed reduction of 10% annually.
DISCUSSION
Even under a series of optimistic estimates, the results
of the simulation show that agricultural production in Eritrea will not be
able to support the projected population after the year 2020. The results of the simulation are preliminary
and dependent on the assumptions used for the analysis. However, such simplified assumptions have allowed
for the parameterization of many of the components and algorithms used in
the model. Although many of the simulated
results are quantitatively uncertain, the qualitative implications of the
analysis are probably accurate. Eritrea
appears to be closing in on its biophysical carrying capacity even with intensive
agricultural inputs.
Future development of the agricultural component of the model will focus on expanding the number of crops simulated in the model and allowing for different levels of agricultural intensity. Additionally, we will be adding subunits that will simulate natural ecosystems as well as industry and trade. The long-term goal of this project will be to create a tool that decision-makers will be able use to test the possible results of proposed development policies. Moreover, the model will include a number of biophysical constraints often overlooked in traditional economic models.
LITERATURE
Hall,
C.A.S., (editor) (2000) Quantifying Sustainable Development. Academic Press. USA..
IGADD, CPSZ Viewer-2000 (1994) Crop Production System Zone
Database Version 1.01, IGADD FAO Agrometerology Group.
Ricardo D. (1817) The principles of political economy and taxation.
G. Bell and Sons. London.
Woldu, T. and R. Van Buskirk (1997) Remote Sensing of Biomass Production, Radiation Distributions, and Rainfall Patterns. Senior Thesis Report, University of Asmara, Eritrea.