Mean monthly wind speed for Adama and Miesso. 14. 5. Mean monthly relative humidity for Adama and Miesso. 14. 6. Mean monthly sunshine hours for Adama ...
ESTIMATING CROP WATER USE AND SIMULATING YIELD REDUCTION FOR MAIZE AND SORGHUM IN ADAMA AND MIESSO DISTRICTS USING THE CROPWAT MODEL
Kidane Giorgis, Abebe Tadege and Degefie Tibebe1
1
Respectively, Ethiopian Agricultural Research Institute; National Meteorological Agency (NMA); and coauthor, Ethiopian Agricultural Research Institute.
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TABLE OF CONTENTS Section
Page Preface
3
Executive summary
4
1
Introduction
5
2
Background information about the study area
6
3
Description of CROPWAT model
7
4
Estimates and implications of the crop water use and yield reduction percentage for agriculture in the Adama and Miesso districts
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5
Summary of crop water use for maize and sorghum crops in some other districts
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6
Implications for agriculture in the country
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7
Conclusion
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References
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LIST OF TABLES Table
Page
1
Planting and harvesting date for maize and sorghum varieties in Adama
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2
Planting and harvesting date for maize and sorghum varieties in Miesso Estimated values of variables used to assess actual crop water use in Adama district
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Estimated values of variables used to assess actual crop water use in Miesso
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3 4
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LIST OF FIGURES Figure
Page
1
Mean monthly rainfall for Adama and Miesso
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2
Mean monthly maximum temperature for Adama and Miesso
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3
Mean monthly minimum temperature for Adama and Miesso
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4
Mean monthly wind speed for Adama and Miesso
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5
Mean monthly relative humidity for Adama and Miesso
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6
Mean monthly sunshine hours for Adama and Miesso
14
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PREFACE The reports in this special series are the result of a multi-country research activities conducted under the GEF funded project: Climate Change Impacts on and Adaptation of Agroecological Systems in Africa. The main goal of the project was to develop multipliable analytical methods and procedures to assess quantitatively how climate affects current agricultural systems in Africa, predict how these systems may be affected in the future by climate change under various global warming scenarios, and suggest what role adaptation could play. The project has been implemented in 11 countries: Burkina Faso, Cameroon, Ghana, Niger and Senegal in west Africa; Egypt in north Africa; Ethiopia and Kenya in east Africa and South Africa, Zambia, and Zimbabwe in southern Africa. The study countries covered all key agro-climatic zones and farming systems in Africa. This is the first analysis of climate impacts and adaptation in the Africa continent of such scale and the first in the world to combine cross-country, spatially referenced survey and climatic data for conducting this type of analysis. The analyses reported in this series focus mainly on quantitative assessment of the economic impacts of climate change on agriculture and the farming communities in Africa, based on both the cross-sectional (Ricardian) method and crop response simulation modeling. The cross sectional analysis also allowed for assessing the possible role of adaptation. Moreover, the project employed river-basin hydrology modeling to generate additional climate attributes for the impact assessment and climate scenario analyses such as surface runoff and streamflow for all districts in the study countries. The Centre for Environmental Economics and policy in Africa (CEEPA) of the University of Pretoria coordinated all project activities in close collaboration with many agencies in the involved countries, the Agriculture and Rural Development (ARD) Department of the World Bank, the World Bank Institute (WBI), the Food and Agriculture Organization (FAO), Yale University, the University of Colorado, and the International Water Management Institute (IWMI). The project received supplemental funding from TFESSD, Finnish TF, NOAAOPG, and CEEPA. We are grateful for the invaluable contributions of all these institutions and all individuals involved in this project. All opinions presented in this report series and any errors in it are those of the authors and do not represent the opinion of any of the above listed agencies. Rashid Hassan, Project Leader CEEPA, University of Pretoria
Ariel Dinar, Project Manager ARD, World Bank
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EXECUTIVE SUMMARY This research report examined the impact of climate change on crop production in two districts based on the FAO CROPWAT model and assessed adaptation measures in those districts. Today climate change is a big issue in any part of the world and affects all human activities. Agricultural practices are affected by climate change, particularly in those countries which are dependent on rainfed agricultural systems. Hence to assess the impact of climate change on crop production and adaptation measures, the CROPWAT model was used to simulate yield reduction for maize and sorghum crops in two districts of Ethiopia: Adama and Miesso. The simulation of yield reduction and estimation of crop water use was based on ten-year crop and meteorological data using the model. The results showed that the water used by crops in both these districts was far less than actually needed, with pronounced effects on the simulated yield reduction percentage. The results show a decrease in yield of 40–70% as a result of the increase in evaporation rate. This yield reduction is caused by climate change. Increased evaporation because of higher temperatures combined with the reduction in rainfall and lower water availability in the soil means that the supply of water does not match the demand. This affects the overall condition of plants and their yield. In response to this situation, various adaptive measures have been undertaken in these districts as well as all over the country. Some of these adaptive measures are: using supplementary irrigation such as small irrigation and water harvesting, minimizing evaporative demand by using mulch, and applying soil moisture conservation techniques and crop management practices that reduce sensitivity to water stress. Most of these adaptive measures are undertaken at farm level. This depends on farmers’ perception of water stress conditions. In the two districts studied, farmers are already aware of the situation and are responding by adopting these measures. They are adjusting planting density and the timing of various operations, and using conservation tillage and intercropping. They are also introducing traditional irrigation and water harvesting methods to cope with the water stress problem during the crop growing period. Currently the government is responding by encouraging change from a rainfed production system to one using irrigation. This is the right way to adapt to the water stress and drought conditions at country level. Many small water tanks are being constructed in the two districts studied and all over Ethiopia to supplement crop production under moisture stress conditions. Efforts to adapt to climate impacts may be modeled on current efforts to mitigate variability. The major difference is that climate change is likely to be permanent, whereas climate variability often takes the form of only temporary setbacks. With climate variability, some solutions can be temporary until the weather returns to normal. However, with climate change, the problems are more permanent and so more attention must be given to permanent solutions.
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1. Introduction In Ethiopia agriculture is the backbone of the country’s economy, with the majority of the population engaged in this sector. However, a wide range of climatic, ecological and topographical diversities influences it. Though Ethiopia has 3.5 million hectares of irrigable land, the irrigated land covers only 160,000 hectares, which is about 3% of the total irrigable land. The dependency of most of the farmers on rainfed agriculture has made the country’s agricultural economy extremely vulnerable to the effects of weather and climate. A failure of rains and the occurrence of drought or consecutive dry spells during the growing season leads to crop failure, which in turn leads to food shortage. Rainfed agriculture depends on the judicious utilization of weather and climate, which are beyond man’s control. A clear knowledge of the available natural resources will assist in short- and long-term agricultural planning. It is very important to know the rainfall distribution of the country. Different annual rainfall patterns are produced as a result of variation in the weather systems and topographic influences. In Ethiopia there are two agricultural seasons. The two rainfall seasons that play a significant role in its rainfed agriculture are the belg and kirmet seasons. The belg season in Ethiopia starts in mid-February and lasts until May and is very important for many crop-growing areas of Ethiopia. It is important for the production of belg crops in the southern Tigray Region, northern Shoa, northern and southern Wello in the Amhara region, northwestern Shoa, Arsi, Bale, the eastern and western Hararghie zones of the Oromiya region and Hadiya, northern Omo and the Kembata Alaba Tembaro (KAT) zones of the SNNPR (Southern Nations, Nationalities and People’s Region). Although the belg season contributes only 5–10% to the country’s overall crop production, it supplies 25–60% of the food needs of the areas mentioned above. It is also during the belg season that the long cycle main season crops – maize and sorghum – are planted. Furthermore, belg is the main rainy season in the pastoral areas of the Borena, Somali and Bale lowlands. In agricultural areas, livestock are affected by the quality of belg rains. The kirmet rainfall season extends from June to September. With the exception of the south, all parts of the country are under the influence of the kirmet rain. The agricultural season during kirmet is known as meher. The meher season contributes about 90–95% of the national crop production. The main crops grown over most of meher producing areas are teff, cereals and pulse crops. Agriculture in the country is exposed to the effect of failure of rains or occurrence of successive dry spells during the growing season, which could lead to food shortage. Though food shortage resulting from adverse weather conditions is not new in this country, it has increased in severity and there have been shortages every two years since 1950. Therefore, an impact assessment should be made and adaptation measures studied to improve agricultural planning and productivity.
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2. Background information about the study area 2.1. District information and agricultural activity Adama Adama is located in eastern Showa in the Oromiya Region. This area is part of the central Rift Valley and dominated by flatlands stretching between the escarpments bordering the eastern and western sides of the Rift Valley. The altitude ranges from 1380m to 1740m. Adama is predominantly categorized under SM2 major (and SM2-5 minor) agro-ecology (i.e., sub-moist mountain and plateau, tepid to cool) (MOA, 1998; Mengistu, 2003). Crop production is the dominant agricultural practice in the area. The major crops are maize, sorghum, haricot beans and teff. Maize accounts for 30% of the cultivable areas of the district. Maize and teff are the most important food staples. Haricot beans are grown primarily as a cash crop and sorghum is used primarily for food and brewing. Other crops grown are barley, Irish potatoes, wheat, lentils and peas. Most of the farmers in the area own cattle, primarily as a source of draft power and as a cash reserve. Broadcasting is the planting method in the area. Intercropping is the common practice for planting: sorghum/maize with haricot beans and sometimes teff with rapeseed. The dryland area is generally monocropped. This is mainly because of the use of long-duration crop varieties. Crop intensity can be increased through intercropping, depending on the characteristics of the land. To minimize their risks, farmers resort to mixed cropping or intercropping. This farming system can produce more over space and time for the multiple needs of the farmers. Intercropping fast-growing legumes such as beans, cowpeas and mung beans also smothers weeds and thus is a considerable help to the base cereal crop. Farmers in the area use the short rainy season from March to May for preparing their land and the longer June to August season for planting their crops. Hence, the busiest time of the year is from June to August, for planting and weeding of teff, planting of haricot beans and planting and weeding of maize (Table 1). Miesso Miesso is one of the ten districts of the western Hararghe zone of the Oromiya region. It is located in the eastern central part of the Rift Valley with altitudes ranging from 1300m to 1500m. The landscape of the area is gently undulating. Miesso is predominantly categorized under SM1 major (SM1-1 minor) agro-ecology (i.e. hot to warm sub-moist plain) (MOA, 1998). The farming system of the Miesso district is dominated by crop production. The major crops grown are sorghum, maize, haricot beans, the oilseed crop sesame, and the perennial crop chat. Sorghum accounts for 66% and maize 24% of the cultivable land and the rest is under other crops. Aleligne (1992) indicates that sorghum is primarily grown for food but may also be sold for cash. Many farmers in lowland areas also grow haricot beans for cash purposes. Pulses are the most common relish crops in the Miesso area. The cropping system of the Miesso district is determined by the rainfall pattern. The rainfall pattern of the area is bimodal, consisting of belg (spring) and meher (summer) rains. Cultivation of crops during the belg season is insignificant and this time is usually used for
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land preparation. Most of the crop cultivation practices depend on the summer rainfall. Mono-cropping is the common practice in the area, with cereals following cereals, though farmers in the area are also practicing intercropping (for crop intensification and often in response to declining farm sizes). Maize with beans, sorghum with sesame in the lowlands, sorghum with beans, and maize with beans in the lower midlands are the common intercropping practices in this district. Chat is also often intercropped with pulses, maize and sorghum. The cropping calendar of the district is as follows. From January to March is the period for land preparation for sorghum and maize, and from May to July for haricot beans. March and April is the planting time for maize and sorghum and August and September for haricot beans. October to December is the season for harvesting the three major crops (Table 2). 2.2. Climate information Both Adama and Miesso have a semi-arid climate with relatively drier conditions in Miesso. Both districts have a bimodal rainfall pattern with a mean annual rainfall of 740 mm in Adama and 520 mm in Miesso, and temperatures ranges from 10oC to 32oC in Adama and 10oC to 33oC in Miesso (see Figures 1 to 6). 2.3. Soil information Adama has three types of soil: andosols, fluvisols and lithosols. The dominant type is mollic andosols (Anm), with a water-holding capacity of 144mm for a 1m depth. Miesso has four types of soil: regosols, lithosols, luvisols and cambisols. The dominant type is eutric regosols (eRG), with a water-holding capacity of 100mm for a 1m depth.
3. Description of CROPWAT model The CROPWAT model developed by the FAO Land and Water Development Division (FAO 1992) is a simple water balance model that simulates crop water stress conditions and estimates yield reduction based on well-established methodologies for determining crop evapotranspiration (FAO 1998) and yield responses to water (FAO 1979). This model has been used to simulate yield reduction percentage as a result of the decrease in evaporation rate. The basic calculation procedure in this empirical model is:
1-Ya/Ymax = ky (1-Eta/Etm) Ya: actual yield Ymax: maximum yield Ky: yield response factor Eta: actual crop evapotranspiration Etm: maximum crop evapotranspiration
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This formula enables the degree of sensitivity to water to be taken into account in estimating yield reductions for various crops and growth stages based on the soil moisture status. The input data for the model are monthly climatic parameters including maximum and minimum temperature, humidity, sunshine and wind speed. The model calculates ETo and estimates of crop evaporation rates, expressed as crop coefficient (Kc), based on wellestablished procedures (FAO 1998). The yield response factor Ky and the depletion fraction (p) were also estimated for selected crops by the FAO.
4. Estimates and implications of the crop water use and yield reduction percentage for agriculture in the Adama and Miesso districts Average yield reduction for maize and sorghum estimated for Adama district were 40.03% and 40.64% respectively. In Miesso district, the estimates were 66.65% (maize) and 66.60% (sorghum) (see Tables 3 and 4). As Tables 3 and 4 show, the crop water use of the selected crops is far lower than the crop water need as indicated by the water stress coefficient (Ks). Moreover, in both districts the yield reduction percentage is higher as compared to maximum yield, especially more than half in the Miesso district. This implies the need for adaptive measures to mitigate the water stress problem of the two districts. Some of the adaptive measures are: using supplementary irrigation such as small irrigation and water harvesting, minimizing evaporation by using mulch, and applying various soil moisture conservation techniques and crop management practices that reduce sensitivity to water stress. Most of these adaptive measures would be undertaken at farm level, but this can depend on farmers’ perception of the water stress conditions. In the two districts farmers are already aware of the situation and are responding by using the techniques mentioned above. They are adjusting planting density, changing the timing of various operations, and using conservation tillage and intercropping. They are introducing traditional irrigation and water harvesting methods to cope with the water stress problem during the crop growing period. Currently the government is responding by encouraging change from a rainfed production system to one using irrigation. This is the right way to adapt to the water stress and drought conditions at country level. Many small water tanks are being constructed in the two districts studied and all over Ethiopia to supplement crop production under moisture stress conditions. In general, the estimated values of crop water use for the two crops suggest that the existing agricultural activities need to change to a less risky production system.
5. Summary of crop water use for maize and sorghum crops in other districts Maize and sorghum are the major crops grown in the dryland areas of Ethiopia and crop production is undertaken under water-stressed conditions. The crop water use of maize and sorghum in some other dryland areas is more or less similar to that of the districts described above, i.e. the crop water need is not being satisfied. As a result crop yields in most dryland
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districts are very low. The average yields in these districts are 1500–2000kg/ha for maize and 2000–2500kg/ha for sorghum.
6. Implications for agriculture in the country The estimated crop water use is an important parameter to use in planning and managing agricultural activities for maize and sorghum crops at country level. The estimated values clearly show that maize and sorghum are being produced under conditions of water stress, with a pronounced effect on yields. This means that different crop and soil water management practices need to be adopted, such as: (i) maximum use of rainfall (water harvesting, runoff reduction, early planting, etc.); (ii) minimizing water loss (evaporation reduction by mulching or rapid crop cover, wind shields, minimum tillage, weeding etc.); and (iii) being water-efficient (planting low water consuming crop species, adapting fertilization to the water available, optimal planting and seeding, selection of varieties that can complete their cycle within the length of the climatic growing period, etc.). These strategies allow a better use of the available water at the farm level. The government should also take responsibility for formulating and implementing policies that will help the agricultural activities of the country to adapt to water stress conditions, for example by constructing medium to large irrigation systems and water harvesting structures. Another important area of work is preparing policies to mitigate the potential damage from climate change. Future climate damage may well resemble the current damage done by climate variability. Efforts to adapt to climate change may be modeled on current efforts to adapt to variability. The major difference is that climate change is likely to be permanent, whereas climate variability often means only temporary setbacks. With climate variability, some solutions can be temporary until the weather returns to normal. However, with climate change, the problems are more permanent and so more permanent solutions must be sought. Strategies for coping with climate variability are providing food assistance, and helping to improve agricultural productivity by applying modernized farm techniques and using irrigation and new crop varieties. These strategies can help farmers cope with marginal environments. Food assistance can help the poor bridge the gap between one good harvest and the next. These strategies are well suited for climate variability. Attempts to address negative climate change impacts may incorporate these same strategies. However, the productivity reductions caused by climate change are far more permanent than those caused by climate variability. Some approaches that are suitable for temporary productivity shortfalls are not as effective for dealing with more permanent problems. For example, food aid is acceptable as a method of dealing with a short-term gap in production. Most countries, however, would balk at providing a permanent supply of food for free to an area that is no longer suitable for agriculture. Consequently, more permanent solutions need to be considered to deal with the more long-lasting problems of climate change in selected local areas. In designing such solutions, the relative advantages of the following need to be considered: (i) maintaining agriculture in affected areas; (ii) providing alternative development strategies; and (iii) encouraging people to migrate away from adverse sites. In general, the above situations mean that the country’s existing agricultural system must be changed to a less risky one.
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7. Conclusion Estimation of crop water use and simulation of yield reduction is essential for implementing risk management at farm level and formulating policies and strategies at national level in response to climate change. Estimations of such parameters are useful for evaluating crop water productivity under prevailing rain patterns and traditional farm practices and in defining farmers’ options for improvement and devising appropriate strategies for optimizing yields and reducing the risk of crop failure related to crop choice, planting time, soil cultivation and crop cultural practices (weeding, planting density, fertilization) and in defining options for water conservation and supplemental irrigation. Finally, estimations of crop water use and simulation of yield reduction provide the information necessary for making decisions about various agricultural activities and allow the assessment of production under rainfed conditions.
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REFERENCES Aleligne K & Regassa E. 1992. Bahir Dar mixed farming zone: Diagnostic survey report. Research report No. 18, Ethiopia Institute of Agriculture, Addis Ababa, Ethiopia. FAO (Food and Agriculture Organization), 1979. Yield response to water. Authors, Doorenbos J & Kassam AH. Irrigation and Drainage Paper 33. Rome, Italy. FAO (Food and Agriculture Organization), 1992. CROPWAT, a computer program for irrigation planning and management. Author, Smith M. Irrigation and Drainage Paper 46, Rome, Italy. FAO (Food and Agriculture Organization), 1998. Crop evapotranspiration : Guidelines for computing crop water requirements. Authors, Allen RG, Pereira LS, Raes D & Smith M. Irrigation and Drainage Paper 56. Rome, Italy. Mengistu, A., 2003. Country Pasture/Forage Resource Profiles: Ethiopia, FAO. http://www.fao.org/ag/agp/doc/counprof/ethiopia/ethiopia.htm MOA (Ministry of Agriculture), 1998, Agro-ecological zones of Ethiopia. Natural Resources Management and Regulatory Department, Addis Ababa, Ethiopia.
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Table 1: Planting and harvesting date for maize and sorghum varieties in Adama Crop type
Planting dates
Harvesting dates
Maize Sinde Katumani Blonde Sorghum Haricot beans
8 May – 23 May 27 May – 28 June 20–28 April 1 June – 20 June 29 June – 20 July
10 September – 30 September 30 August – 25 September
Table 2: Planting and harvesting date for maize and sorghum varieties in Miesso Crop type Sorghum Gobiye 76-T1-23 Abshir Maize Melkassa-1 Katumani Haricot beans Mexican Awash-1
Planting dates
Days to maturity
Harvesting dates
15–30 June 15–30 June 15–30 June
90–100 90–120 90–120
15–30 September 1–15 October 15–30 September
15–30 June 15–30 June
90 110
15–30 September 1–15 October
20 June – 10 July 20 June – 10 July
80–100 75–90
20–30 September 20–30 September
Table 3: Estimated values of variables used to assess actual crop water use in Adama district Crop
Maize Sorghum
ETo mm/period
ETm mm/period
Ky
Ya Kg/ha
Ym Kg/ha
563.08 469.02
531.60 469.02
1.25 0.9
2257 2671
3500 4500
Ks
Area cropping intensity
0.72 0.55
ETa mm/period 382.75 257.20
Table 4: Estimated values of variables used to assess actual crop water use in Miesso Crop
Maize Sorghum
ETo mm/period
ETm mm/period
Ky
Ya Kg/ha
Ym Kg/ha
425.55 352.7
374.80 352.7
1.25 0.9
1422 1500
3500 4500
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Ks
0.53 0.26
Area cropping intensity
ETa mm/period 198.64 91.70
Mean Monthly Rainfall
Rainfall (mm)
250 200 150
Adama
100
Miesso
50 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Months
Figure 1: Mean monthly rainfall for Adama and Miesso Mean Monthly Maximum Temperature 34
Temperature(oC)
32 30 28
Adama
26
Miesso
24 22 20 Jan Feb Mar Apr May Jun
Jul
Aug Sep Oct Nov Dec
Months
Figure 2: Mean monthly maximum temperature for Adama and Miesso Mean Meanthly Minimum Temperature
Temperature (oC)
19 17 15 13
Adama
11
Miesso
9 7
Ju l Au g Se p O ct N ov D ec
Ja n Fe b M ar Ap r M ay Ju n
5
Months
Figure 3: Mean monthly minimum temperature for Adama and Miesso 13
Mean Monthly Wind Speed
Wind Speed (m/s)
4.0 3.5 3.0
Adama Miesso
2.5 2.0 1.5 1.0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Months
Figure 4: Mean monthly wind speed for Adama and Miesso
Relative Humudity(%)
Mean Monthly Relative Humidity 80 70 60
Adama
50
Miesso
40 30 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Months
Figure 5: Mean monthly relative humidity for Adama and Miesso Mean Monthly Sunshine Hours
Sunshine Hours(hr)
10 9 8 7
Adama
6
Miesso
5 4 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Months
Figure 6: Mean monthly sunshine hours for Adama and Miesso
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