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“Effects of Climate Change on Agriculture Particularly in Semi-

Arid Tropics of the World with Some Examples of selected areas of

Ethiopia”

Almaz Demessie

Meteorological Research and Studies Team Leader, National Meteorological Agency, Addis Ababa Ethiopia,

2008

Abstract

Today climate change is a burning issue all over the world because of its global nature. Fears have

arisen that; climate may be changing for the worse and its impact on agricultural production,

which will reduce the supply of food to growing population, especially in developing countries.

Climate change would affect various human activities. Agriculture is one of the activities, which

can e seriously affected by climate change. Due to high inter-annual variability and uneven

distribution of rainfall during the rainy season, recurrent droughts have observed in semi-arid

tropics of the world over the last three decades. As White, (cited in Climate Variability and

Agriculture by Y.P Abrol, S. Gadgil and G. B.Pant 1996) pointed out rain fed agriculture in the

semi-arid tropics is limited mostly by high climatic variability with principal limiting factor being

rainfall. The main crops of traditional rain fed agriculture are sorghum, millet, maize, cowpea,

pulses, and sesame. Adverse climatic conditions are the bottleneck of Ethiopia’s rain fed

agriculture development. Besides, agricultural production suffers from periodic outbreak of pests

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and diseases, both pre- and post harvests, in most parts of Ethiopia. Some pests are becoming a

serious problem in some areas where the rainfall condition is erratic. For instance, Sorghum

Chafer becomes a chronic problem since 1993 over northeastern highlands of Ethiopia including

Afar regions.

The objective of the research study is to identify and characterize the effect of climate change on

agriculture by assessing the climatic condition of the selected areas and its effect on agriculture.

1. Introduction

Climate is the average weather parameters, usually 30 years of a given locality. The

measures of climate include mainly the estimates of average values of weather

parameters and measures of variability near to the average value. As Biswas, (cited

in Climate Variability and Agriculture by Y.P Abrol, S. Gadgil and G. B.Pant 1996)

has stated in most cases, some deviation of average values between two reference

periods is mainly due to large weather variability. There may be real shifts of the

average or changes in variability between two periods. These deviations from the

mean value constitute climate variation or change. Adverse climatic conditions are

the bottleneck of Ethiopia’s rain fed agriculture development. As a result,

particularly in drought prone regions of Ethiopia agriculture production is

determined by climate variability. The rainfall variability in the rainy seasons is the

most serious problem encountered by Ethiopian farmers. Therefore, it is very

important to clearly understand the characteristics of weather parameters together

with the triggering factors that exert significant impacts. The main crops of

traditional rain fed agriculture are sorghum, millet, maize, cowpea, pulses and

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sesame. There is a suggestion that increased CO2 will benefit temperate and humid

tropical agriculture more than that in the semi-arid tropics. During the process of

photosynthesis plant species with the C3 photosynthetic pathway tend to respond

positively to increase CO2 while the C4 have a poor response. Since C4 plants are

mostly tropical crops, the situation will be worst over the areas (Parry, 1990).

Besides, agricultural production suffers from periodic outbreak of pests and diseases,

both pre- and post harvests, in most parts of Ethiopia. The factors involved here are

principally wind, precipitation and temperature. Some pests are becoming a serious

problem in some areas of Ethiopia where the rainfall condition is erratic. For

instance, Sorghum Chafer becomes a chronic problem since 1993 over northeastern

highlands of Ethiopia including Afar regions. Climate change will alter the nature of

occurrence of agricultural pests in terms of area. Warmer temperatures shorten the

generation time; increase the development rate of epidemic.

Many research studies have stated that meteorological parameters like rainfall,

temperature and wind play an important role in changing agricultural production

more than other parameters. Any deviation from the mean climatic condition would

affect agricultural activities negatively. Agriculture can show little sensitivity to

moderate variations around those means. If the condition persisted a bit longer it

could affect the overall physiological activities of the plants and result in crop

damage and final yield reduction. The examples presented in this paper are selected

randomly from pastoral and crop producing areas just to indicate the situation of

climate change in some areas of Ethiopia.

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Length of Growing Period (LGP) is describing the period during which crop growth

is not affected by climatic constraints, i.e. the period of the year when water

availability allows crop growth and when the temperature is not limiting crop

growth. As many studies have indicated, the duration of the period in which rainfall

exceeds selected levels of evapotranspiration is the most useful index of agricultural

potential. This period refers to the length of time during which water and

temperature permit crop growth. As FAO (1991) stated, three specific values are

identified for climatic classification, namely: arid, with LGP of less than 75 days;

Seasonally dry, with LGP of between 75 and 270 days; and humid with LGP of more

than 270 days. Annual or seasonal rainfall is traditionally used to describe the supply

of water to crops, because it is the primary measurement particularly for rain fed

agriculture. Nevertheless they should be supplemented by the information in which

the availability of water, now more easily obtainable by the concept of reference

evapotranspiration (ETo). Where sufficient water is available, crops need specific

periods to accumulate the energy necessary to complete their growth and

development. In this study, in addition to the above methodology, Nieuwolt’s (1981)

approach of an agricultural rainfall index (ARI) will apply. In this approach instead

of mean monthly rainfall 80% probability of exceedance (dependable rainfall) is

important to determine LGP in which periods with ARI value greater than 100

considered as growing season. Many researchers agree that 80% probability of

rainfall is dependable for the continuation of vegetative growth if the rainfall amount

at that level of probability is sufficient for plant growth. Consideration of 80%

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probability level is important to identify a specific area in terms of moisture

availability, because it covers a longer period (i.e. 8 out of 10 years). In this study,

both approaches will test. From the analysis, I try to figure out the shift in mean

values, LGP and ARI for the selected stations, which is the major indicator of

climate change.

2. Materials and Methods

The purpose of this study is to analyse the effect of climate change on agriculture by

using different meteorological parameters and different types of crop models and

statistical analysis in order to investigate the influence of climate change on crop

performance in terms of crop production and protection aspect of Ethiopia.

a. Meteorological Data

More than 30 years data used for the analysis of climate change. All elements are

used which are important for the calculation of ETo such as maximum temperature,

minimum temperature, Relative Humidity, Sunshine hours and wind speed mm/sec.

b. Crop yield data

Yield data taken from different Ethiopian Central Statistics Authority year Books.

Cumulative yield amount of major cereal crops like maize, sorghum, tef, barley,

wheat and millet was taken to assess the change in crop yield. Thirty years data was

available; however, there is a gap in some years.

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c. Statistical Methods

Excel used for simple statistical analysis like for the calculation of mean and mean

deviation including trend analysis. The percent probability analysis was done for the

cropping season. The statistical analysis used to indicate variability is percent

deviation from the mean:

((Actual-Mean)/Mean)*100) (c.1)

In addition, to indicate percent probability of rainfall the methodology that was

developed by Dorenbos and Pruitt (1977: cited in Technical Note 179) was used. It is

the ranking order method; each record is assigned a ranking number (m). The

ranking numbers are then given probability levels Fa (m), which is calculated as

follows:

Fa (m) =100m/ (n+1) (c.2)

d. FAO CROPWAT (Version 4.3) Model

The FAO Penman Monteith as modified by FAO (1994), which is described in

http://www.FAO.ORG/AG/AGLW/WCROP.HTM for the calculation of reference

evapotranspiration (ETo). The definition of reference evapotranspiration is “the

rate of water loss from a short green crop fully covering the ground and fully

supplied with water”. As FAO in many studies has pointed out Penman Monteith

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method overcomes shortcomings of the previous FAO Penman method and provides

values more consistent with actual crop water use.

The data used for the calculation of ETo is on a monthly basis i.e. monthly maximum

and minimum temperature (ºC), mean relative humidity (RH%), wind speed (m/s),

sunshine hours. Other data like elevation, latitude, longitude and Julian day i.e. day

of the year from January.

The other statistical method to calculate ten daily ETo values (Figure 10) is Instat

Version 3.22

e. FAO Methodology to calculate Length of Growing Period (LGP)

LGP is expressing the period during which crop growth is not affected by climatic

constraints or it characterizes the period of the year when water availability allows

crop growth and when the temperature is not limiting crop growth. The method to

calculate LGP is FAO methodology by Frere and Popov (1979). “The growing

period (GP) is defined as the time (days) during a year when precipitation exceeds

half the potential evapotranspiration (PET) plus the time (days) necessary to

evapotranspire 100mm of water (or less if 100 mm is not available) from excess

precipitation stored in the soil profile. The period during which the daily mean

temperature value is less than 6.5°C is subtracted from the length of the period

during which water is available”. However, in this study, daily values of temperature

were not available. As a result, ten-day mean temperature is considered in place of

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daily mean. Besides, Nieuwolt (1981, cited in Technical Note 179) methodology that

was introduced as an Agricultural Rainfall Index:

ARI = 100* P/ETo (e.1)

Where P is 80% probability of exceedance of rainfall. In this case, 80% probability

of exceedance for the rainfall season will be applied instead of mean annual rainfall.

According to his concept-growing period is considered when ARI is over 100.

4. The Effect of Climate Change on Agriculture

Climate affects agriculture in many ways. Effects due to increased atmospheric CO2

concentration, CO2 induced changes of climate and rises in sea level are the major

ones. Many research studies have stated that meteorological parameters like rainfall,

temperature and wind play an important role in changing agricultural production

more than other parameters. Rising emission of carbon-dioxide, methane, nitrous

oxide and other radioactive gases (Greenhouse Gases) will lead not only to an

increase of surface temperature of the earth but also a change of precipitation (Parry

et al, 1990). Thus, this condition could have a significant negative impact on

agriculture.

Any deviation from the mean climatic condition would affect agricultural activities

negatively. Agriculture can show little sensitivity to moderate variations around

those means. If the condition persisted a bit longer it could affect the overall

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physiological activities of the plants and result in crop damage and final yield

reduction. As a result agriculture becomes particularly sensitive to climate change.

For example, weak monsoon rain in 1987 caused significant decreases in crop

production in India, Bangladesh, and Pakistan (World Food Institute, 1988).

As Fig. 1 indicates, there is a shift in mean values and decease in mean amount of

rainfall during the second period mainly. Thus, this condition can clearly shows the

effect of climate change in the area.

As can be seen from figures 1 and 2 there is a decreasing trending in mean decadal

rainfall amount during 1976 - 2006 in most cases. Besides, the percent deviation of

mean annual rainfall shows negative deviation in most cases as of 1979.

As the FEWS NET report (October 6, 2003) indicates(Figure 5), the precipitation in

the long cycle region (areas mainly grown long cycle crops like maize and sorghum)

shows a negative trend by 5.4 mm per year. Thus, this situation can have negative

impact on agriculture, thereby decreasing yield production year to year significantly,

since the Ethiopian agriculture mainly depend on rainfall amount and distribution.

If we see the overall rainfall condition over the country, it shows a decreasing trend

(Fig 5), thereby the crop yield showing decreasing trend year to year (Fig. 3).

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5. Crop Water Requirement of Plants

Climate variability can have significant affect on the availability of water to semi-

arid ecosystems. As Parry (1990) pointed out a doubling of ambient CO2

concentration causes about 40% decrease in stomata openings in both C3 and C4

plants, which may reduce transpiration by 23-46%. This condition would favour

areas where water is a limiting factor, such as in semi-arid regions. Nevertheless,

there are many uncertainties, like how much the greater leaf area of plants as a result

of increased CO2 will balance the reduced transpiration of each plant will increase

in case of irrigated crops. Besides, increased CO2 can induce abnormal and erratic

rainfall distribution, which would affect the normal process of water requirements of

crops, and this situation leads to poor crop performance.

When we see figure 6 there is a shift in Length of Humid Period (LHP). With regard

to LGP we can see a better length of LGP in case of Mean 2 (the extension is about a

month). Thus, better crop performance could be possible in LGP 2.

Some researches pointed out that a doubling of atmospheric CO2 concentrations

from 330 to 660 ppmv cause 10 to 50% increase in growth and yield of C3 crops

(such as wheat, soybean and rice) and a 0 to 10% increase for C4 crops (ibid).

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6. Crop Growth Rates

Temperature is the dominant climatic factor in the development of plants and animal

growth. Any variation beyond the optimum level has a negative impact on the

normal growth and development of plant. As Parry (1990) pointed out recent studies

indicated that an increase in temperature resulted in lower yields in cereals and the

reverse was true for root crops and grassland. However, due to higher rate of

evaporation and reduced moisture availability, which could be created by the global

warming, the overall yield will be less.

As can be seen from figure 7 there is a rise in mean maximum temperature

continuously and from figure 8 the percent deviation moves towards positive value

year by year that means the maximum temperature shows increasing trend year by

year thereby shows changing temperature. This is obvious that the increased

temperature amount has a great contribution for the rise of reference

evapotranspiration (ETo). Thus, a rise of ETo together with a decrease in rainfall

amount over the area would have negative impact on LGP; thereby decreasing crop

yield is inevitable since the agricultural activities mainly dependent on rainfall in

Ethiopia.

7. Growing Seasons

As Parry (1990) has stated, the effect of warming on length of growing season and

growing period will vary from region to region and from crop to crop. In tropical

climates, in which there are less seasonal temperature changes, the amount of

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available moisture often determines the periods of plant growth; in the rainy season,

growth is luxuriant and in the dry season, many plants become dormant. As a result

in this case the variation in temperature amount is more serious in mid and high

latitude regions. For instance, it is estimated that the growing season of wheat will

extend by ten days per °C in Europe and in central Japan by about 8 days pre °C. In

general the conclusion is that increased mean annual temperatures, if limited to two

or three degrees, could generally be expected to extend growing seasons in mid-

latitude and high-latitude regions. Increases of more than this could increase

evaporation rate, which leads to reduced soil moisture and limit the growing season.

For the analysis of Agricultural Rainfall Index (ARI), 80% probability of exceedance

taken for the rainfall season instead of mean monthly rainfall and mean monthly

Reference evapotranspiration (ETo) is the other component to analyze ARI.

According to this concept the growing period is considered when ARI is greater than

100. Thus, from this analysis we can see sift in Length of Growing Period (LGP) as

we compare ARI 1 to that of ARI 2. There is an extension of LGP in case of ARI 2.

When we see the LGP analysis of Negele (figure 10), during the first rainy season

there is a decrease in Length of Humid Period (LHP) as well as LGP. In case of the

second rainy season there is a decrease in LHP and amount of rainfall during the

first, second and third dekad of October ranging from 6-11 mm as well whereas we

can see similar condition in case of LGP in both periods.

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Various phenological models have predicted that generally the length of growing

period of the crop plants would be reduced as a result of higher temperature caused

by GHG (Alocilja and Ritchie, 1991; Roberts et al, 1993; Gangadhar Rao and Sinha,

1994 cited in Climate Variability and Agriculture by Y.P Abrol, S. Gadgil and G.

B.Pant 1996). Due to this condition, the total dry matter accumulation period also

will be reduced. Moreover, as Kroff et al (cited in Climate Variability and

Agriculture by Y.P Abrol, S. Gadgil and G. B.Pant 1996) have pointed out that, an

increase in temperature will reduce not only the total duration, but the dry matter

production also.

8. Pest and Disease

Global warming leads to a change in the nature, habit, and distribution of pests.

Studies suggest that temperature increases may extend the geographic range of some

insect pests currently limited by temperature.

The effect of climate warming plays an important role on the distribution of pests.

In Ethiopia, the most susceptible areas for insect out breaks are apparently the

highland regions below 2000 meters and parts of lowlands. However, plant pests

occur everywhere during the rainy season particularly at the time of drought when

erratic rainfall is a common phenomenon over drought prone areas of the country.

Pests at present limited to tropical countries may spread into the temperate regions

causing serious economic losses. For instance, Sorghum Chafer becomes a

chronic problem since 1993 over northeastern highlands of Ethiopia including

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Afar regions. Climate change will alter the nature of occurrence of agricultural

pests in terms of area. Warmer temperatures shorten the generation time; increase

the development rate of epidemic. Most agricultural diseases have greater

potential to reach severe levels under warmer conditions. Higher precipitation and

warmer air temperature would increase the spread of fungal and bacterial

pathogens in given areas. Cereal crops are more susceptible to pest and diseases

under warmer and humid conditions.

9. Adaptation

Adaptation has the potential to reduce adverse impacts of climate change and to

enhance beneficial impacts. The capacity of human nature to adapt to and cope with

climate change depends on such factors as wealth, technology, education,

information skills, infrastructure, access to resources, and management capabilities.

Thus, the adaptation capacity of developing countries will be limited due to their low

level of technological advancement. Therefore, intergovernmental activities are

important in order to perform sound adaptation measures.

e. Possible Adaptation Measures

Applying improved knowledge to develop better techniques and to

resist the effect of climate change in a given locality.

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Cultural practices that can precondition for the plant need to be

further explored and implemented to mitigate the effect of stress

factors.

Change in land use by using deferent techniques such as changing

farm area, change to crops with higher thermal requirements and

drought-tolerant crop, a switch to crops with lower moisture

requirements and changes in crop location.

Change in management in terms of the use of irrigation, fertilizer, in

the control of pests, in soil drainage, in farm infrastructure.

Create awareness among people about the causes of climate changes

so that farmers could change their wrong management practices such

as deforestation, over grazing, etc. which are the main causes for

desertification and climate change at large.

10. Conclusion

Climate change induced by increasing greenhouse gases is likely to affect crop yields

differently from region to region across the globe. Decreases in potential crop yields

are likely to be caused by shortening of the crop-growing period, decrease in water

availability due to higher rates of evaporation. As many studies suggested, the

tropical regions appear to be more vulnerable to climate change than the temperate

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regions for several reasons. Temperate C3 cops are likely to be more responsive to

increasing levels of CO2 than C4 cops. Besides, insects and diseases, already much

more prevalent in warmer and more humid regions may become even more

widespread. Tropical regions may also be more vulnerable to climate change because

of economic and social constraints. Greater economic and individual dependence on

agriculture, widespread poverty, and inadequate technologies are likely to exacerbate

the impacts of climate change in tropical regions. Thus, plant breeders should give

more emphasis on development of heat and drought-resistance crops. Research is

needed to define the current limits to these resistances and the feasibility of

manipulation through modern genetic techniques. In some regions, it may be

appropriate to take a second look at traditional technologies and crops as ways of

coping with climate change. Better management techniques in crop and livestock

production should be developed in order to mitigate the effect of climate change. In

order to avoid mismanagement of natural resources like deforestation, overgrazing,

and cleaning farmland by using fire, etc creating awareness among farmers has great

importance.

As can be mentioned in the above statement, those with the least resources have least

capacity to adapt and are the most vulnerable. Thus, since the effect of Global

Worming affects both developing and developed countries intergovernmental

economic support is very important to tackle the problem and to achieve sound

solution for climate change. In many cases, reducing vulnerability to current climate

variability should also serve to mitigate the impact of global warming.

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evapotranspiration - Guidelines for computing crop water requirements.

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Carter, T. R., Konijn, N. T. & Parry, M. L. (1988), The Impact of Climate Variations

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Doorenbos, J. & Kassam, A. H. (1979). Yield Response to water. FAO Irrigation and

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Frere, M. & Popov, G. F. (1986). Early Agro meteorological Crop Yield Assessment

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http://www.climatenetwork.org/

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Appendix 1: Figures

Figure 1 Shows difference in monthly mean rainfall between two periods (1961-1991 and 1976 – 2006) for Jijiga

Figure 2 Shows percent deviation from the long years mean rainfall for Jijiga

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Fig. 3 Shows crop yield for major cereal crops of Ethiopia

Fig. 4 Shows % deviation from the mean yield from 1953/4-2001/02 Source FEWS.net October 6, 2003 Fig.5 A decrease in rainfall amount over long cycle crop growing region

Average April-September precipitation in the western long cycle crop-growing region (shaded region on map)

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Fig. 6 Shows comparison of Length of Growing Periods and Length of Humid Period during two different periods [(1953 – 1982) with (1976 – 2006)] for Mychew

Fig. 7 Trend analysis of mean maximum temperature for Bahir Dar from 1961 – 2000 during the cropping

season (May – November)

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Fig. 8 Shows percentage deviation from the mean dekadal maximum temperature for Bahir Dar (1962-2001)

Fig. 9 Agricultural Rainfall Index (ARI) during two different periods

(From 1962 – 1992 and 1975 - 2005)

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Fig. 10 Length of Growing Period during two different time frames

[(1954 – 1983 and 1976 - 2006)