Local Climate Variability and Crop Production in the Central Highlands of Ethiopia

Local Climate Variability and Crop Production in the Central Highlands of Ethiopia

Arragaw Alemayehu*1 and Woldeamlak Bewket1

*1Corresponding author

Department of Geography & Environmental Studies

Addis Ababa University

Email:

1Department of Geography & Environmental Studies

Addis Ababa University

Email:

Local Climate Variability and Crop Production in the Central Highlands of Ethiopia

Abstract

The aim of this study was to understand the association of crop production with climate variability in the central highlands of Ethiopia. Production data of five major crops at the Enumeration Area (EA[1]) levelfor the main cropping season (Meher) were collected from the Central Statistical Agency (CSA). Correlation analysis shows that crop production and cultivated area are positively correlated with rainfall, but negatively associated with maximum and minimum temperatures. Regression results indicating rainfall to be the most important determinant of production levels. It is concluded that current climate variability has a significant influence on crop production in the area and any unfavorable change in the local climate in the future will have serious implications for household level food security. Efforts to adapt to the ongoing climate change should begin from tackling the current climate variability and take a climate risk management approach for adapting to the ongoing climate change.

Key words: climate variability; crop production; North Shewa, Ethiopia

1. Introduction

Climate variability plays a great role in agricultural prodcution having a direct impact from the start of land preparation to the final harvest (Akinseye et al., 2013; Mesike and Esekhade, 2014). Rainfall in particular is a critical climatic element. While non-climatic factors like availability and access to farm inputs, land quality, tenure security, infrastructure, market and policy can be managed by farmers or the government in the short- or long-term, little could actually be done to drastically change the influence of climate, particularly rainfall. Mesike and Esekhade (2014) note that rainfall has always dictated how land is used and plays a dominant role in agriculture exerting a direct impact on production and spatial distribution of crops.

In countries like Ethiopia where agriculture is dependent on rainfall, the influence of climate variability on crop production is generally large. Previous studies have shown that variability in Ethiopia’s agricultural GDP is clearly correlated with rainfall variability (World Bank, 2006; Bewket, 2009). Segele and Lamb (2005) also note that the characteristics of the main rainy season (June – September, known as Kiremt) rainfall are the most important determinants for agricultural activity from the perspective of its amount and geographical coverage. On the other hand, the frequent droughts in the past 30 years were caused by shortages of rainfall.

Whereas rainfall variability has always been a major challenge to Ethiopia, Kiremt rainfall is less variable in most parts of the country compared to the short rainy season (March – May, known as Belg) which is highly variable (Shankoa and Camberlin, 1998; Bewket and Conway, 2007; Ayalew et al., 2012;Mengistu et al., 2013). Abebe (2006) notesthat Belg rainfall is highly variable and its impact on agriculture of this variability is higher in the onset period than the cessation period. The sensitivity of agricultural production to current climate variability is a very important indicator of the vulnerability of Ethiopian smallholder farmers to ongoing climate change.

Many studies have shown the importance of rainfall variability in explaining crop production fluctuations at different spatial scales. At the global level,estimates are that climate variability accounts for roughly a third of observed crop yield variability (Ray et al., 2015). At the continental level, climate variability is widely recognized to be a major driver of crop production fluctuations particularly in Africa, where agriculture is predominantly small scale and rainfed (Jones and Thornton, 2003;IPCC, 2014). For instance, Rowhani (2011) and Afifi et al (2014) reported that intra-annual and inter-annual variability of rainfall and temperature had significant impacts on crop production and thereby food security of communities in Tanzania. In Nigeria, rainfall variability was found to have a significant influenceon crop production (Adamgbe and Ujoh, 2013; Akinseye et al., 2013; Yamusa et al., 2015). In Uganda, variations in rainfall and temperature had significant effects on crop production (Mwaura and Okoboi, 2014).

There are only a few studies on the effects of climate variability on crop production in Ethiopia (Admassu, 2004; Lemi, 2005; Bewket, 2009). These studies are either at national or regional scales which mask local scale variability. Admassu (2004) studied the impact of rainfall variation on crop production for the whole of Ethiopia.The results of this study show no significant correlation between total annual, Kiremt and Belg rainfall, and production of those crops (barley, maize, sorghum, tef and wheat) in most parts of the country. Lemi (2005) investigated correlations between crop yields and rainfall covering some parts of the country (former provinces of Gojjam, Gonder, Harargieand Keffa). His results show that significant correlation exists between rainfall and yields of crops during the two seasons and noted the significant impact of rainfall variability on crop yields in almost all provinces. Bewket (2009) studied the relationship between rainfall variability and crop production in the Amhara region, and reported existence of significant correlations between crop production and rainfall and concluded that farmers are vulnerable to food insecurity partly due to rainfall variability in the region. Regardless of scale, high correlation coefficients between rainfall and crop production have been found by these researches.

Teka et al. (2012) investigated relationships between rainfall variability and crop and livestock production in eastern Tigray, northern Ethiopia. They found a positive correlation between livestock holding size and crop yield with rainfall amount. Another study was the work of Rosell and Holmer (2007) on implications of rainfall change for Belg harvest in South Wollo, north-central Ethiopia. They found significant effect of rainfall variability on food security of communities and changes in farming situation in the past 40 years. However, they only used agricultural data obtained from farmers’ interviews on what they could remember in the study years rather than using actual data on crop or livestock production.

There is no local scale study, as is attempted here, on local scale climate variability and crop production in the country insofar as it is known to the authors. In this study, unlike the previous researches, crop production data are at the EAs level and climatic data are at a spatial resolution of 10x10 km. The general objective of the study is to analyze the influence of current climate variability on crop production in the central highlands of Ethiopia by using three districts as case study sites.The specific objectives are: i) to assess inter-annual variability and trends in crop production, and ii) investigate correlations of crop production with rainfall and produce a surface map showing the spatial patterns of the associations.

1. Materials and Methods
2. Description of the Study Area

The study covers three districts (Woredas in Amharic), namely Menz Gera Meder, Basona Werana and Efratana Gidim, of the North Shewa Administrative Zone of the Amhara National Regional State (ANRS) of Ethiopia (Fig. 1). According to the Central Statistical Agency (CSA) (2013) the total population of the three districts is371,890 out of which 188,820 are males and 183,070 are females. Menz Gera Meder is in the Dega (highland) agroecological zone while Basona Werana and Efratana Gidim are in the Weyna Dega (midland) and Kolla (lowland) agroecological zones, respectively. Elevation ranges from 1140 m asl in Efratana Gidim to 3554 m asl in Menz Gera Meder. Some 37% of the total area of the three districts is mountainous, 21% is rugged terrain and 42% is plain lands. Based on the FAO/UNESCO soil classification system, Vertisols cover about 37% of the districts, Nitosols cover about 24%,Chernozems cover about 30% and others some 9%. The major land use types include croplands (46.6%), forest and bush (22.7%), and grazing (10.4%) %)(North Shewa Zone Agriculture Office, 2013). Annual rainfall is >1000 mm and mean annual temperature ranges from 13.5 0C in Basona Werana to 21.5 0C in Efratana Gidim(Alemayehu and Bewket, Submitted).

Mixed farming is the dominant livelihood source in the area. Selling local alcoholic drink (Araki), fuel wood, charcoal and the multipurpose Guassa grass (a species of the Festuca genus of perennial tufted grasses used for livestock feed, traditional house construction, and home to many endemic species of fauna and flora of the Afroalpine ecosystem) are used to supplement local livelihoods. Most of the districts in the North Shewa Zone are food insecure, and the problem is worse in the Dega agro-ecological zone(North Shewa Zone Food Security Coordination and Disaster Prevention Office, 2013). According to information from the Zone’s Food Security Coordination and Disaster Prevention Officeand discussions with key informants, large parts of the Zone are beneficiaries of the Productive Safety Nets Program, which is a food security program of the government. Environmental challenges such as occurrence of droughts and floods, land degradation and declining soil fertility have contributed to the deterioration in the livelihood of smallholder farmers in most of the districts of the Zone. Socioeconomic and demographic constraints also aggravated the livelihood challenges. The Zone belongs to one of the most vulnerable areas to climate change and variability in the country where a large segment of its population is already food insecure (North Shewa Zone Food Security Coordination and Disaster Prevention Office, 2013).

Figure 1: Location of North Shewa Zone in the ANRS, Ethiopia

2.2 Data and Methods

The data used for this study are historical rainfall and temperatrue records and time series data on production of five major crops:barley (Hordiumvulgare), maize (Zea mays), sorghum (Sorghum bicolor), tef (Eragrostis tef) and wheat (Triticum aestivum) grown in the area for the main cropping season, locally known as Meher(any temporary crop harvested between September and February). The rainfall data are for 132 points on 10×10 km grids reconstructed from weather stations and meteorological satellite records and cover the period between 1983 and 2013.The maximum and minimum temperature data are for the same grid points but cover period between 1981 and 2011. The rainfall and temperature data were collected from the National Meteorological Agency of Ethiopia.

The reconstruction was made by the National Meteorological Agency of Ethiopian and the International Research Institute for Climate and Society of Columbia University, USA. Reading University, UK made the calibration and validation of the data. There is a strong correlation (r =0.8) between the station and satellite-derived data indicating the reconstructed gridded data are of good quality to analyse climatic variability and trends in the country.

Enumeration level data on crop production were collected from the Central Statistical Agencyfor the period 2004-2013, for which relatively good quality data are available.The production data are generaetd from a sample survey of smallholder farmers with area cultivation in hectares and total production in Quintals (a Quintal is 100 kg). The short rainy season, Belg season, production is not included in this study for two reasons: (i)its contribution to the annual total is not significant in the study area; it ismuch less than its national average contribution; and (ii)the Belg season crop production data were available only for five years (2001-2005).

To determine production variation, relationship and effect of climatic variables, namely rainfall (monthly, seasonal and annual rainfall totals)and temperature (maximum and minimum) on crop production in each district, bivariatecorrelation and multiple linear regression analyses were used. The regression model for a single crop in a given district was calculated as:

Ywt=a+b1x1wt+b2x2wt+b3x3wt+bnxnwt (1)

Where;

Ywt= the value of the dependent variable (crop production) in districtw in year t;

a = Y intercept

b1, b2, b3, ··· bn = regression coefficients

x1, x2, x3, ··· xn = the independent variables (monthly, seasonal and annual rainfall totals, and minimum and maximum temperatures).

Correlation and regressions techniques are important in showing the relationship between climatic parameters and crop production, and to identify the most predictor variable. Lemi (2005); Bewket (2009); Tunde et al. (2011); Rowhani (2011); Adamgbe and Ujoh (2013) and Akinseye et al. (2013) used the same methodology in their study of the relationship between climate variables and crop production.

To analyse spatial correlations between the climatic elements and crop production, both the climate and crop data were rasterized to generate surface data by the simple kriging interpolation technique using ARCGIS 10.1 software. This is because simple kriging interpolation technique takes account of the spatial correlation pattern with the least interpolation error (Beck et al., 2005).

To supplement the information obtained from quantitative sources,focus group discussion and key informant interviews were conducted; three focus group discussions, each with eight members, and three key informant interviews were conducted in each district. In addition, field observation and document review were used to augment the data.

1. Results

3.1Rainfall andCrop Production Correlations

3.1.1 Variations and trends in Crop Production

Cereals are the dominantly grown crops in Ethiopia not only in terms of the area under cultivation but also amount of production and consumption (CSA, 2014). More than 73% of the country’s cropped area and over 68% of the crop production are contributed by cereals. From the cerealstef, maize, sorghum, wheat and barley are the main food crops in the country in terms of area of land coverage and contribution to the country’s production. They are produced under rainfed farming system. Sorghum and maize are long-cycle and warm weather cerealswhile wheat, barley, and tef are short- cycle cool weather cereals (CSA, 2014).

Production data of the five meajor cereals namely, barley, maize, sorghum, tef and wheat and cultivated land under each crop atEA level over the period 2004-2013 are used in this study. Barley and wheat are by far the most produced cereals in the area. Barely was the single most important crop for Menz Gera Meder which accounts for about 54% of area covered and 47% of production during the Meher season over the study period. The second important cereal in this district was wheat which accounts for 26% of production and 36%of cultivated area, respectively.Wheat and barley are also intensively produced cereals in Basona Werana which accounts for more than 46% and 35%, respectively, of total meher cereal production. According to focus group discussion participants, the major emphasis for barley was its low input demand, particularly chemical fertilizer; adaptability to infertile and degraded soil; and suitability to the local agroecology. On the otherhand, in Efratana Gidim, tef and sorghum are the dominant cereals which account for 65% and 20% of total cereal production, respectively,during Meherfor the period under study.

Sorghum and wheatproductions show high year-to-year variations. Wheat (CV=101%) and barley (CV=99.8%) production in Basona Werana show high year-to-year variation with standard deviations of 17 Q/year and 9 Q/year, respectively. Sorghum (CV=118%) and tef (CV=113%) production show high year-to-year variation in Efratana Gidim with standard deviation of 12 Q/year and 9 Q/year. Compared to others, Menz Gera Meder shows less year-to-year variation in the production of crops. However, wheat (CV=76.8%) followed by barley (CV=76.1%) show high year-to-year variation with standard deviations of 6 Q/year and 8.5 Q/year, respectively. Bewket (2009) also reported high coefficient of variation for sorghum following high variability of rainfall in the lowlands in the Amhara Region. On a global level study, Ray et al. (2015) observed that maize shows the highest coefficient of variation accounted by climate variability.

In terms of trends, barley, wheat, tef and sorghum showed statistically non-significant decreasing trends at the rate of 1Q/ha, 1Q/ha and 2.5Q/ha, respectivelywhile no trend was observed for maize in Basona Werana. This is in a similar trend with the climate data which showed significant declining trend of annual rainfall and warming trends in the maximum and minimum temperatures. Further, information from the Zone’s Food Security Coordination and Disaster Prevention Office and discussions with key informants revealed that productivity of the area has declined from time to time due to natural and human factors, and large parts of the Zone have become beneficiaries of the Productive Safety Nets Program, which is a food security program of the government.

Despite the fact that crop production is expected to increase in the cooler and mountainous areas where wetter conditions and warmer temperatures are expected (IPCC, 2014), land degradation, soil erosion and soil nutrient depletion may, however, result decreasing trends in most crops in the area.