1. Climate Variability Coping Mechanisms in ElKhwie Area, Northern Kordofan- Western Sudan. By Ahmed H. I. Elfaig & Eltaieb Ganawa Faculty of Geographical and Environmental Sciences, University of Khartoum

2. Introduction: The Climate system is dynamic, complex, varies and operates across wide scale. Climate variability and climate change are intermingling terms. Climate change mean change in climate variables i.e. statistical distribution of climate variable change. The change or great fluctuation in climate elements such as rainfall, humidity and temperature have profound effects on traditional production system and traditional producers ( traditional farmers, pastoralists and agropastoralists).

3. The climate variability in this study more or less focuses on rainfall variability over both space and time. The traditional producers have developed certain mechanisms to cope with climate variability.

4. Problem of the Study During the 1960s the study area characterize by dense vegetation cover, rich palatable grasses, high amount of rainfall (up to 550mm) with low rainfall variability (Table 1). During the 1990s the situation changed and the area characterized by sparse plant cover, vulnerable environment, high water deficiency, high rainfall variability, frequent rainfall failure, and prolonged drought as 19984-1991

5. yearsrainfall/mm 1961320 1962450 1963330 1964550 1965450 1966350 1967289 1968350 1969300 1970315 Table 1

6. These variables present major indicator of climate variability. In order to survive and to sustain this variability the traditional producers have used their indigenous knowledge to develop and adopt certain mechanisms to cope the effects of climatic variability. The adopted coping mechanisms contributed positively to the processes of environmental degradation.

7. Objectives of the study 1.To study rainfall variability as the major indicator of climate variability 2.To show how the local people perceive climate variability within the context of environmental degradation. 3.To study the coping mechanism adopted by the traditional producers to cope with climate variability. 4.To highlight some indicators of environmental degradation as a result of rainfall variability

8. Study Boundaries This study covered the period 1960-2000. The geographical location:

10. Background: The available study showed great variability in the climate through out Sudan (map 1, 2 and Table 2).

11. Scale:1 to 12,000,000 Climate Variability Isohyets shift Sources: National Drought and Desertification Uinit 1994

12. Climate Variability: Rain Fall averages

13. Rain fall averages of 30 years through 1961 - 2000 indicates progressive decline Station 1941 - 1970 1951 - 1980 1961 - 1990 1971 - 2000 Karima42.732.421.312.7 Khartoum164.1159.7140.3121.4 Elfashir271.6244.1209.7194.7 Kassala313.7292.9265.2247.2 Elobeid405.7377.5309.2332.3 Elgadarif581.1593.4598.1613.3 Elgineina581.6543.0440.6399.6 Juba990.6968.2940.0954.2

14. In the study area (ELSamani 1984), indicated that there was better quality vegetation including both more perennial and greater diversity in composition of high value trees and grass species but many of these grasses diminished. UNEP’s report (19997) concluded that in that 25 years about 61 million ha 24% were degraded.

15. The degradation and changes have let to severe losses in life stock and fluctuation of crop production. Elmahi 1986 and AbuSin 1990 the problem of environmental degradation in the sudano- sahelian including the study area can be explained by its fragile environment, high rainfall variability, drought and increase in human and animal’s population. The usage of the satellite’s imagery can clearly marked degraded and more vulnerables.

16. Methods of Data Collection and Analysis: The sampling procedures followed geared towards drawing representative samples and to avoid bias in the selection procedures. The selection of these sites based on the following: 1.There are most populated sites in the region. 2.Similar in their occupation structure

18. Sample size House hold sample was conducted in the study area Subsequently a total of 500 house hold were selected randomly. Data were collected through filed survey and questionnaire-interview

19. Rainfall Data Record Two nearest metrological station were chosen Namely Elnouhod and Elobeid station. Rainfall record since 1961-2000 were used to show the degree of variability and fluctuation.

20. Analysis of Rainfall Variability The rainfall records of the selected stations were examined; – The period divided into two equal parts 1961- 1979 and 1980-2000 – Arithmetic average between the two interval was contrasted to explain the degree of variability through the time intervals.

21. – The formula here after was used: (X1-X2)*100/X1 X1= average of the time period 1961-1979 X2= average of the time period 1980-2000

22. Using the formula mentioned above to explain the degree of change: result showed that the change during this time is 2.62% and it is inconsistent

23. Table2: Rainfall Amount and Variations at Ennuhud Station YearsMax rainfall amount Min rainfall Amount AverageStdev 1961-196955029836085 1670-197959028037395 1980-198939315032182 1990-200045518236990

25. Table3: Rainfall Amount and Variations at Elobeid Station YearsMax rainfall amount Min rainfall Amount AverageStdev 1961-1969 1670-1979 1980-1989 1990-2000

27. Results and Discussion Demographic characteristics was examined (sex, age, Occupation and etc….) Data on sex revealed that 933% of the respondents were male and 77% was agro- pastralists and rest were traditional farmers, on the other side 25% understood that environmental degradation is a decreased and fluctuation of Rainfall

28. Respondent’s of the Environmental Change PerceptionAll Variables considered No. % Only One variable considered No. % Ranking Change in vegetation 45691.215230.41 Decrease and fluctuation of rainfall 36372.612124.22 Buried of depression and water resources 155315210.45 Decreased in soil fertility 29859.695193 Decreased and change in crop productivity 17234.460124 No idea56122046

29. Coping Mechanisms The coping related to agriculral practices reflect the comprehensive knowledge of the traditional producers about their surrounding environmental conditions. The main objective behind that to reduced vulnerability to environmental changes to secure food (short term) and livelihood (long term)?????

30. This can be achieved through reducing exposure or mitigating the impact. In agricultural side the coping mechanism range from simple Ramail to quick maturing varieties and cultivation in different directions Coping mechanism reflect coping with variability and decreased in rainfall, delay in rainfall arrival, and long dry spell, they also reflect coping with decreased and fluctuation in crop productivity.

31. These mechanism are: 1.Early land clearing 2.Ramail 3.Wide spacing 4.Shaliekh mechanism 5.The wedding 6.Intercropping 7.Shift to quick maturing varieties 8.Cultivation of vast area in different directions

32. Livestock coping mechanism 1.Herd diversification 2.Movement of agro pastoralist 3.Animal birth control 4.Livestock raising system

33. Other Coping mechanisms: 1.Moral Economy: Solidarity ZAKATT 1.Selling of Assets

34. Conclusion: Climate variability is wide spread phenomena. The climate variability is clearly understood by the local producers. The major indicators of climate variability is variations and fluctuations in rainfall. The adopted coping mechanism (ACM) support the traditional producers to survive, still not sustainable for long term. The ACM contributed positively to environmental changes.

35. Recommendations Construction of models to predict the furure behavior of climate based on climate variables, using Remote sensing to help in evaluation of current situation and predicting the future. Coping strategies rather than prevailing adaptation and coping mechanism. The Coping strategies should focus on both traditional agricultural production system and animal raising. Design of observation system to monitor the climate system by using new technologies for monitoring and assessment. Production of database and climate models to visualize the variables of climate accessing the digital data.