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close this book Measuring drought and drought impacts in Red Sea Province
View the document Acknowledgements
View the document A Note on Orthography and Other Conventions
View the document Executive summary of the research
Open this folder and view contents 1. Introduction to Red Sea Province
Open this folder and view contents 2. Measuring drought and food insecurity in Red Sea province: in 1987 and 1988: a technique for Pthe rapid assessment of large areas. Roy Cole
Open this folder and view contents 3. Drowght, food stress, and the flood and rainfall record for Red Sea Province. Roy Cole
Open this folder and view contents 4. Drought, the market, and the impact of food aid in Red Sea Province, 1980 to 1989. Roy Cole
Open this folder and view contents 5. Nutritional status of children in Red Sea Province, November 1985 to November 1987. Mary Cole and Roy Cole
Open this folder and view contents 6. The nutritional status of children in Red Sea Province, July-October 1989: a supplement to the November 1985-November 1987 results. Mary L. Cole and Roy Cole
Open this folder and view contents 7. Land tenure, agricultural labour, drought and food stress in the Gash, Gash Dai and Tokar agricultural areas. Roy Cole
Open this folder and view contents 8. Changes in tree density on five sites in Red Sea Province: early 1960s to 1989. Roy Cole
Open this folder and view contents 11. Conclusion
View the document Technical glossary

Measuring drought and drought impacts in Red Sea Province

Edited by Roy Cole

Research Officer

Oxfam Port Sudan

December 1989

 

Acknowledgements

Working in the Sudan during the two years of my tenure as Research Officer for Oxfam Port Sudan has been a challenge. There were many times, particularly during the latter part of my tour, when we could not find food in the market for our field trips not to mention for our daily subsistence. I owe a debt of gratitude to my staff for their willingness to continue to work in such conditions and to subsist on so little. Without their hard work and daily sacrifices none of this work would have been possible.

It has been a rare privilege to work for Oxfam. There are few other organisation in the world like it in terms of its responsible, hardworking staff and its unique relationship with the poorest of the poor. The cooperation and important contributions to the papers in this collection by the Sudanese government is much appreciated. A particular word of thanks is due the National Water Corporation, the Gash Board, the Tokar Delta Board, the Meteorological Department, and the Sudan Survey Department.

I would like to thank the following people for their comments on earlier drafts of these papers: David de Pury, Sam Gonda, Olivia Graham, Andy Jeans, Adrian Rayson, Ilona Sulikova, and Willie Wint. Particular thanks goes to those who attended three days of discussion of the penultimate draft: Safaa Agib, Mary Cole, Fatima Gebreil, Maurice Herson, John Low, Margaret McEwan, Peter Tilley, and Martin Walsh. I would also like to thank David Bourn for his insightful comments over the last two years, June Stephen for document support, and Randy Wilson for computer support. The views expressed in this book are those of the author and not necessarily those of Oxfam.

I hope that our contribution will be of use in understanding drought, food stress, culture, and economy in Red Sea Province and will contribute circumventing future emergencies.

 

 

A Note on Orthography and Other Conventions

The editor has endeavoured to follow the orthography adopted by modern Arabists throughout this collection of papers. However, some commonly used words in English, for example, "Arabian", have been spelled without the 'ayn marker, ""'. Other Arabic words that are commonly spelled a certain way in English are spelled according to that spelling. For example, "suudaan" has been spelled "Sudan", alkhartuum has been spelled Khartoum. The spelling of proper names was done on a case by case basis according to preferred spelling by the person in question. For example, if an author cited spells his name Osman instead of 'uthmaan, the accepted spelling by Arabists, I have used the spelling preferred by the person cited For all other words I have used the Aribists' spelling. I have followed, incidentally, the Arabic system of alphabetising authors, first name, father's name, grandfather's name, rather than attempt to adopt the western family name system.

I have preserved the definite article, "al" throughout, even before the haruuf ashshamsiva in order to avoid confusion. For example, al Sa'ud is used instead of asSa'ud. It should be noted that Sudanese pronunciation differs from Modem Standard Arabic pronunciation in the following sounds:

qaaf for qaaf

qaaf for ghayn

siin for thaa° or deal for thaa°

zaay for thaal and thaa°

zhaa° for dhaadh

The list below represents the symbols used throughout the present collection of papers. Shadda, or gemination, is represented by a doubling of the consonants as in, for example, the word shadda itself. The long vowels, alif, waaw, and yaa° when acting as a seat for hamza have been transcribed in the short vowel form with °, hamza, immediately following as in gabaai°1, "tribes". Admittedly, this method presents some awkwardness in such words as lu°lu°, "pearls". These short vowels are: fatha, dhamma, and kasra respectively. Sukuun has not been transliterated nor has wasla

'

the consonant 'aye.

°

the glottal stop, hamza.

aa

the long vowel alif.

a

the short vowel fatha, madd alif, alif maqsuura, and taa° marbuuta.

aw

the dipthong fatha waaw.

ay

the dipthong fatha yaa°

d

the short vowel dhamma.

dh

the consonant dhaadh.

g

the consonant qaaf (except for administrative terminology or where the Modern Standard Arabic "q" is more appropriate).

gh

the letter ghayn.

h

the consonants haa° (aspirated) and haa° (unaspirated).

i

the short vowel kasra.

iin

the third person plural suffix.

iw

the dipthong kasra waaw.

kh

the letter khaaf.

s

the consonants siin and saadh, and, depending on the word, thaa°.

sh

the letter shiin.

th

the letters thaal and thaa°.

uu

the long vowel waaw between two consonants.

uw

the dipthong dhamma waaw.

uy

the dipthong dhamma yaa°.

w

the long vowel waaw in initial position or after a long vowel or the short vowels fatha or kasra.

y

the long vowel yaa° and the nisba suffix.

z

the consonants thal and zaay.

zh

the consonant zhaa°.

Spelling of words in Tu Bedaawi has followed the Arabic pattern. With sounds that have no equivalent in Arabic the nearest equivalent in English was used.

 

 

Executive summary of the research

When I was appointed Research Officer for Red Sea Province in January 1988, I was given a wide brief: to develop a research programme to measure drought and recovery for Red Sea Province. A related and very important part of my brief was to make Oxfam's relief food allocation system accountable. To accomplish these tasks I chose key areas and key variables to obtain reliable information on vegetation, the market, rainfall and flooding, agriculture, livestock, malnutrition, and the regional economy. I adopted a historical approach to address these topics in order to understand the past and present environmental and economic trends, to provide the necessary historical contrasts to interpret the present, and to contribute some depth to the work of researchers to come who may not have the time or opportunity to investigate difficult sources.

The papers which follow are a product of two years of research done by the Research Section of Oxfam Port Sudan from early 1988 to the end of 1989 and four years of research done by the Oxfam Port Sudan Nutrition Research Teams. Each of the eight papers is intended to address one element which singly, or in conjunction with other factors, affects food security in Red Sea Province. In the conclusion common themes are brought together in a brief discussion of the findings of all the papers.

The first paper is a general introduction to Red Sea Province: its physical geography, rainfall, political organisation, infrastructure etc; the activities and way of life of the people who live there, how they cope with drought and organise their society, plus an overview of famine relief in the province.

Paper two, "Measuring drought impacts and food insecurity in Red Sea Province in 1987 and 1988: a technique for the rapid assessment of large areas", is an examination of drought and socioeconomy in Red Sea province in 1987 and 1988 through a spatial framework. The structure used in the assessments and the assessments themselves form the basis of Oxfam's relief food allocation system in Red Sea Province. The study motivated by a desire to make relief food allocations accountable, to obtain more information about the province, and to investigate methods. Watson's (1976) ecozones were used as the basis for an assessment of each zone on six variables: two representing drought impacts and four representing food insecurity. Results, not surprisingly, indicate that 1988 was much better than 1987 but not in all places. There is still high food insecurity in places where refugees have concentrated (although areas infested by locusts had bad scores as well).

The third paper, "Drought, food stress, and the flood and rainfall record for Red Sea Province", examines the rainfall record for 19 gauging stations and the flood record for 9 flood gauging stations. The purpose of this paper is to document the periods and patterns of drought in the past, define what constitutes drought in terms of the historical record, and examine this record in conjunction with the human historical perception of drought. The results indicate that some famines commonly held to have been caused by drought were caused by other factors that weakened the economic strength of people in Red Sea Province such that normal environmental variation became deadly.

Paper four, "Drought, inflation and the impact of food aid in Red Sea Province, 1980 to 1989", examines the changes in market prices for cereals and livestock from 1980 to 1989. Results of the study show that the terms of trade of cereals to goats, the common currency of trade in Red Sea Province, fumed against goats in 1984 in the markets studied but that in 1985 cereal prices declined dramatically and the terms of trade turned in favour of goats. The results of the study suggest that free, province-wide relief food deliveries in early 1985 were responsible for the 56 percent drop in the market value of cereals in 1985 and its continued depression until 1988 when other forces contributed to extreme cereal (and all other commodities) price inflation. The paper also discusses the continued usefulness of free, province-wide relief food deliveries and the impact of new policy associated with the change in government in July 1989 on the cereals and livestock markets.

Paper five, "Nutritional status of children in Red Sea Province, November 1985 to November 1987", examines the data collected by Oxfam since 1985 throughout Red Sea Province on the nutritional status of children under five years of age. Once in 1985 and three times a year in 1986 and 1987 two teams of nutritional researchers surveyed the entire province. Findings of the analysis suggest that the nutritional status of children in Red Sea Province improved significantly with some important exceptions. Rural Port Sudan and North Tokar Districts had children of better than average nutritional status did not improve between 1986 and 1987. More disturbingly, children in Haya District, who had poor nutritional status did not improve between 1986 and 1987. The highest risk of malnutrition was in babies and weaning children. This extends our concern about nutritional status to pregnant and lactating women. Clear seasonal trends in malnutrition rates were seen in the south of the province and not in the north, where there is less rainfall variability. There was no correlation between the World Food Programme relief ration and the nutritional status of children. The effect of the individual settlement explained a large proportion of the variation of the percent weight for height in children in Red Sea Province. The researchers recommend that pregnant and lactating women and babies and children of weaning age are in need of targeted nutritional interventions. Improving the health and welfare of these groups should become largely a gender issue.

Paper six, "Nutritional status of children in Red Sea Province, l989", is an update to 1989 of paper number four. Delays in fieldwork prevented the analysis of these data with the 1986-87 data. Results indicate that nutritional status in Red Sea Province has improved significantly since 1987, however, the same groups identified as at risk in the 198-87 study were found to be still at risk. Gender differences became more apparent in 1989 and deserve further investigation.

Paper seven, "Land tenure, agricultural labour, drought and food stress in the Gash, Gash Dai and Tokar agricultural areas", presents the regional economy of southern and central Red Sea Province, focusing on the Tokar and Gash Deltas. Land tenure and agricultural labour and the role of the two agricultural schemes in food security strategies of the people of Red Sea Province is examined in the paper. Results of the study show that sharecropping is a rational risk-minimising economic strategy that assures a food entitlement even in a highly variable environment such as that represented by the Tokar Delta and the Gash Dai. Where the environment is less variable, such as the Gash Delta, wage labour arrangements predominate. Both agricultural schemes were found to contribute significantly to the regional economy and to strengthen rather than weaken the ability of pastoralists to cope with drought through the provision of thousands of feddans of grazing, vast quantities of crop residues, cereals, and employment.

Paper eight, "Changes in tree density on five sites, Red Sea Province, 1960s to 1989", is a study of change in tree density from the early 1960s to 1989 on five study sites located around the province. The results of the study indicate that dramatic negative changes in tree density have taken place on the study sites in the last 25 years. The findings suggest that the changes are attributable to human rather than environmental impacts. The implications for development work in the province, particularly restocking, are serious.

 

 

1. Introduction to Red Sea Province

The section below is intended as a general introduction to the papers that follow for those unfamiliar with the Sudan and Red Sea Province. It is not a literature review and was not written for the specialist. Those with some expertise on the Sudan and Red Sea Province may skip over this section.

The Sudan, the largest country in Africa, is composed of nine Regions: Bahr alghazal, Central, Darfur, Eastern, Equatoria, Khartoum, Kordofan, Northern, and Upper Nile. The Red Sea Province, the northern half of the Eastern Region, located in the extreme northeast of the Sudan, is almost the same size as Britain; they measure 217000 and 230000 km2 respectively. The Province is situated between 17 and 23 degrees north of the Equator and 33 to 38 degrees east of Greenwich. Through Red Sea Province is the only outlet for Sudan to the sea (see Map 1.1 below). The mountainous province rises like an island out of the monotonous plains of southern Eastern Region and descends abruptly onto a narrow coastal strip.

 

Physical Geography

The Red Sea Hills are located from Egypt to Eritrea in a belt that runs in a north-south direction from about 15 km west of the Red Sea coast to about 150 km inland. The highest peaks of the mountain range are found along the Eritrean border (9100 feet), northwest of 'Aruus at Jebel Oda (7412 feet), southwest of Muhammed Qul at Jebel Erba (7274 feet), and southwest of Halaib town at Jebel Asoteriba (7272 feet). West and southwest of the Red Sea Hills leading to the Nile and 'Atbara valleys are vast monotonous plains sometimes punctuated by tall solitary mountains.

The Red Sea Hills are part of the Red Sea Rift Valley formed by the divergent movement of the Arabian and the North African crustal plates. These plates, units of crust floating on a bed of heated, plastic mantle, are being pushed apart by the formation of new crust along the mid-Red Sea ridge, located at the bottom of the Red Sea aligned in a north to south direction.

The Red Sea Hills are commonly referred to as being composed of Pre-Cambrian crystalline rock. This means that the rock is of the oldest known on earth, formed in the geological era called the Pre-Cambrian over 570million years ago. The Red Sea Hills are composed principally of gneiss and granites shot through during more recent times by vertical wall-like structures of other igneous rock in what are termed "dykes" by geologists. Many dykes are easily visible on the surface. Particularly picturesque pink granite dykes are found along Khor Sitareb in


Map 1.1. Africa and Red Sea Province.

North Tokar District. Gold, mined in Red Sea Province since Pharaonic times, is found only in the dykes. Emeralds are also found in such formations, however, there are no currently working emerald mines in Red Sea Province. Columnar basalt is visible throughout the province particularly in the south and southwest.

There are two alluvial fans of note in the province located along the Red Sea coast: the Arba'at and Tokar deltas. The Arba'at delta is located just north of Port Sudan and the Tokar Delta is located 150 kilometres to the south of Port Sudan. Although both deltas are used for agriculture and pastoralism and provide a measure of security against adversity, the Tokar delta is by far the more important of the two resources. The delta soil is particularly rich. It has been estimated by the Tokar Board that an average of four inches (about 9 cm) of new silt is deposited on the delta every year. This reduces the necessity for the use of fertilisers in farming.

 

Precipitation

Precipitation in Red Sea Province is light. The heaviest rain falls in the southern portions of the province. The Red Sea Hills, running in a north-south direction about 15 kilometres on average from the Red Sea Coast and extending about 150 kilometres inland, exert a positive influence on condensation and rainfall.

Rain falls in Red Sea Province as a result of two atmospheric mechanisms: the northward movement of the InterTropical Convergence Zone (ITCZ) in the summer and the dominance of the Northeast Trade winds in winter. The map below illustrates the rainfall isohyets for Red Sea Province in millimetres.


Map 1.2. Rainfall Isohyets in Fled See Province.

 

Political organisation

Political organisation in the Sudan observes the following hierarchy: the State ( al-dawla), the Region (al-iqliim), the Province (al-muhaafazha), the District (al-majlis), District Council (al-baladiyya), and the Village Council (al-qariyya). The Red Sea Province is divided into seven administrative districts exclusive of Port Sudan: Derudeb, Halaib, Haya, North Tokar, Rural Port Sudan, Sinkat, and South Tokar. District areas vary enormously (see the map below). The head of each District is the District Officer (dhaabit al-majlis) who administers the District through the District Councils. The District Council is administrated by the Administrative Officer (dhaabit al-idaara). Below this level are two more levels of representation at the village level. The 'umda represents the maximal lineage (the tribe) which may be composed of more than one village or settlement and the shaykh represents the minimal lineage which may also include more than one village or settlement. The principal official duty of the shaykh is to collect taxes on animals. In Red Sea Province deliberative bodies are situated at the Village, District Council, District and Provincial levels.

 

Infrastructure, economic activities, and employment

The transport infrastructure of Red Sea Province is weak but good compared to the rest of the Sudan with the exception of Khartoum Province. Port Sudan is the rail terminus for the whole of the Sudan. Rail lines snake across the province from Port Sudan to 'Atbara and then to Khartoum to the south and Egypt to the north. Another rail line runs from Haya, between Port Sudan and 'Atbara, to Kassala and then to Khartoum. All weather road linkages between Port Sudan and the rest of the country are good. Local infrastructure, with the exception of Port Sudan itself, Halaib town which is linked to Egypt by a tarmac road, and the rail and road links designed to service the central part of the Sudan, is poorly developed. Travel is difficult and sometimes impossible during the rainy season. Map 1.3 below presents the road and rail infrastructure of Red Sea Province in graphic form.

Markets in and around Red Sea Province provide goods, buyers for rurally-produced commodities, and employment. There are seven formal markets around Red Sea Province and four outside the province boundaries of importance. These markets are Port Sudan, Tokar, Sinkat, Haya, Derudeb, Gebeit, and Halaib in Red Sea Province and Kassala, 'Atbara, and Aswaan outside the province. Port Sudan is by far the largest market in the province and a variety of domestic and imported commodities can be found there. There are a variety of informal markets around the province. Most of these specialise in certain goods, for example the roadside market south of Delay station where artisanal goods made from duum palm leaves (sa'af) may be found and local sorghum. Another example of a common form of market found along the coast in small settlements such as Ashat Souk, Abu Ramad, or Shalatayn are the small shops selling goods brought into the Sudan outside the auspices of the government.

Most towns in Red Sea Province have secular single-sex primary schools. Gebeit, Haya, Port Sudan, and Sinkat have secular single-sex intermediate schools for boys and girls. Port Sudan has the only higher secondary schools; one for each sex and the Comboni School.

Religious schools (khalwas) are ubiquitous throughout the province. Teachers in Red Sea Province come from all over the Sudan. Teaching posts in the province are coveted because Red Sea Province is considered a hardship post. Two years teaching in Red Sea Province qualifies a teacher to be seconded to Oman where the pay is much better than in the Sudan (Cole 1988).

Barriers to the education of rural and many urban children exist in Red Sea Province. There are not enough schools around the province to satisfy demand, the language of instruction is Arabic rather than Tu Bedaawi, uniforms are required, and, with the exception of a few boarding schools and Tokar town school, no meals for children are provided. Any one of these hurdles alone would pose a difficult obstacle to the enrolment and successful completion of primary and secondary school; together they mean almost no rural children go to secular school. In addition to these barriers, the rural people have themselves placed obstacles in the way of secular education; they regard secular education as sinful. They prefer instead to send those of their male children whom they want to educate to religious schools (khalwa). With the exception of one khalwa near Gebeit, female children are not educated in religious schools.

Manufacturing is for the most part concentrated in Port Sudan where an oil refinery, tire factory, textile mill, flour mill, bottling plant, salt production plant, and motorised vehicle assembly plant are located. Shipping and activities related to the port are the principal economic activities carried on in Port Sudan. Most goods are shipped from Port Sudan to other parts of the country by lorry or train. Oil is transported by lorry and pipeline to Khartoum. Warehousing is a major activity in Port Sudan.

There is a large informal service sector in Port Sudan that provides goods and services to the Port Sudanese. The most notable of these services are the vast cattle feedlots located just north of Daym al-wuhda which provide milk and other livestock products for the city. Other services are the well-articulated system of water distribution, the many small shops, bakeries, coffee houses, and restaurants and the numerous fuel and rural products retailers scattered around the city. Post Sudan has a large quarter, Daym al-warsha (Workshop Quarter), dedicated to minor industry. Here such trades as vehicle repair, welding, blacksmithing, and other metal-using industries are practiced. Suakin, in decline since the bulk of trade, warehousing and shipping moved to Port Sudan in the early part of this century, has been the object of a recent renovation effort since the port in Port Sudan has become crowded.

There are three prisons in the province, two located in central Port Sudan and the other in Suakin, sixty kilometres to the south. There are four gold mines in the province, three in Halaib District and one in Haya District north of Musmar at Hasay. In Halaib District, there is an abandoned iron mine near Tumaala, an abandoned iron mine near Fudikwan, an abandoned chromium mine near Khor 'is, an abandoned manganese mine, and several abandoned emerald mines. There is an abandoned lead mine north of Haya town and an abandoned copper mine near Khor Arba'at in Rural Port Sudan District. These mines, with the exception of the emerald mines and the Fudikwan iron mine, were ordered closed when Numairy took power in 1969 and have never reopened. These mines are apparently still workable and the quality of the ore is reputed to be good For example, the iron content in the ore at the mine near Tumaala is 78 percent. There is a gypsum quarry in Derudeb District and Halaib at Ait, two salt evaporation plants outside of Port Sudan, a brickworks in Tokar, an agricultural scheme in the Tokar Delta that provides thousands of jobs, and a fishing industry along the Red Sea. Oyster beds exist along the coast and were once farmed near Dungunab near Muhammed Qul. The Japanese firm that was exploiting the oyster beds closed down because of a disease-related decrease in the oyster population. A cement factory is scheduled to be built in Derudeb in the near future.

The transport industry has a large service sector built around it that extends from the servicing of vehicles in Port Sudan and along the highway to Khartoum to providing food and shelter to the crews of the lorries and other motorists. This industry has grown considerably since the construction of a surfaced, all-weather road from Port Sudan to Khartoum in the early 1980s.

Employment for the people who live in the rural areas revolves around herding, farming, artisanal production of commodities, and migratory wage labour to the city, towns, or the Tokar, Gash or Khashm al-girba agricultural schemes. It must be stated that the majority of the people in Red Sea Province live in the towns (ERGO 1989) and move from town to country to farm, graze their livestock, or obtain charcoal, fuelwood, et cetera. A minority migrate seasonally to the Nile River. Artisanal industry predominates in rural Red Sea Province. In the south of the province where the duum palm grows a artisanal industry of mat, basket and rope making exists. Duum nuts as well as the fruit of Ziziphus spina-christi are sold in most southern and central markets as snacks and, in the case of the duum nut, as animal food as well. Duum trunks are transported by camels (increasingly by lorry) to bulking points along the Port Sudan to Khartoum highway for eventual sale for use in construction. The Duum palm trunks are prized because they are termite resistant. In the Khor Baraka and Khor Langeb basins where tamarisk grows, an industry based on forest products has developed in addition to mat, basket and rope making. Fuelwood and charcoal are produced as well as beds and poles suitable for constructing the typical Beja rural dwelling, a loaf-like tent made of duum palm mats supported by a framework of tamarisk poles. Small numbers of individuals manufacture charcoal and produce firewood throughout the province. Charcoal making is done on a commercial scale in the 'Udrus and Agwamt basins and in the more wooded areas of the Red Sea Hills within approximately 100 kilometres of urban demand. In northern Red Sea Province people collect and export medicinal plants (harijan) to Egypt.

A word must be said about smuggling. It is a very important industry in the province. The rural areas are crisscrossed with deeply incised smugglers' roads. Smuggled goods into Red Sea Province include consumer goods such as televisions, radios, household goods, and clothes, as well as vehicles, alcohol, drugs, and weapons. Goods smuggled out of Red Sea Province include livestock, cereals and cotton. The government is making courageous efforts to stem this loss of revenue.

Map 1.3 below presents the political districts, towns and transport infrastructure of Red Sea Province.


Map 1.3. Districts, towns and transport infrastructure, Red Sea Province.

 

Agriculture

Agriculture is one of the two principal land uses in Red Sea Province. With the exception of Khor Arba'at and the Tokar Delta, cultivated area is extremely variable around the province from year to year. Principal crops grown are sorghum (durra), millet (dukhn), cotton, and vegetables. The greatest area is devoted to the principal staple, sorghum. Planting is done by two men using a dibble stick (saluuka). Two medium sized floods are needed before planting takes place. In general in arid and semi arid areas about 100 cm of soil moisture is necessary for millet to complete its growth cycle. Sorghum, less drought resistant than millet, requires slightly more soil moisture. The growth cycle of the variety of sorghum used in Red Sea Province is four months. The growth cycle for millet is about three and one-half months. Planting, particularly in the interior of the province, is done on bunds, or sand dams, called teras (from the English "terrace"), built against the flow of water to impede its flow in order to increase soil moisture. In good years cultivation is done along the general course of a khor but in poor years cultivation is restricted to the sand dams.

In the interior of the province planting begins in September or October, depending on the floods; it can even begin in August. In the Gash Delta, planting may begin earlier. Harvesting in the interior of Red Sea Province begins at the end of November or December and extends for about two months. It may continue until March in the Gash if the year is particularly good. Depending on the soil moisture plants are spaced from 0.75 to 1.5 metres apart. Plants are generally spaced at 0.5 m in the Gash.

Coastal agriculture, with the exception of the Tokar Delta, is somewhat different from that practiced in the interior of the province in that the principal period of cultivation is the winter. If there is good rainfall high in the Red Sea Hills during the summer, early floods will irrigate agricultural areas along the coast, thereby lengthening the agricultural year considerably. Spacing of plants is from 1.5 to 2.0 metres. Along the coast, principally along Khor Akwaat, vegetables are increasingly being grown along with the traditionally grown sorghum.

Vegetables are also grown along Khor Arba'at and in the Khor Arba'at Delta. Pumps and mechanical water diversion are used to irrigate the vegetables. The gardens along the khor are located in the areas of deposition; along the inside of bends in the streambed. Dates and citrus trees are also grown along the khor.

In the Tokar Delta a variety of crops are grown: cotton, sorghum, millet, and vegetables (see paper 8 for further details). Agriculture is more reliable in the Tokar Delta than elsewhere in the province because there are floods from June to September (or October) and also winter rainfall. Soil moisture from the floods is used to bring a crop to about mid-way through its growth cycle and the rains bring the crop to maturity. The origin of Khor Baraka (as well as Khor Gash) is high in the Eritrean mountains and this assures greater reliability of flow from year to year. The map below presents the distribution of agricultural areas in and around Red Sea Province.

Cultivation in Khor Baraka is principally of millet, although some vegetables are grown for home consumption. Planting is done after farmers have estimated that the highest flood of the season has occurred. This period can range from August to October, depending on the year. The usual planting month is September. The fringes of the floodplain are planted first, then closer to the main stream as the flood season comes to a close. Harvesting begins at the end of December an can extend to March. Spacing between plants is from 1.50 to 2.0 metres.


Map 1.4. Agricultural areas in Eastern Sudan.

There are several commercial vegetable gardens located at the apex of the delta at Dulubiay.

Porn Sudan is the principal market for the agricultural products of Red Sea Province. Agricultural products are imported from Kassala and Wad Medani in the Sudan and from outside the country as well. Cereals are locally produced and/or may come from the Gash Delta, Khashm al-girba, or Gedarif. There are four sources of vegetables for the Port Sudan market: Tokar, Khor Arba'at, Kassala, and Wad Medani. From the Wad Medani area tomatoes are imported to Port Sudan for most of the year. Tokar and Khor Arba'at tomatoes and other vegetables become available in the autumn. Vegetables become difficult to find in the summer.

 

Pastoralism

Pastoralism is the second principal land use in Red Sea Province. It should be considered with agriculture as a unit because the major activity of people in the rural areas of the province is agropastoralism. Both activities form the economic basis for survival, although there are other important economic activities. Many of the products of agriculture are used in support of livestock. Indeed, if the harvest fails one still has the stalks from the crop to either sell or feed to the livestock to help get them through the dry season.

There are several strategies employed by herders in semiarid and arid environments to minimise the risk of losing their livestock and to recover if they do. There are other strategies than those listed below. For further information see Cole (1982) and Widstrand (1975).

1. Movement.

2. Herd splitting.

3. Herding different types of livestock.

4. Mutual aid.

5. Social mechanisms of wealth redistribution.

6. Economic diversification.

Pastoralism in most areas of the arid and semiarid world would not exist without movement. The greatest strategy a herder has to minimise risk is to spread risk over space by moving his animals to areas of good and varied grazing. Annual movement, or transhumance, can be classed as either vertical or horizontal. Vertical transhumance is from lowland to mountain and back again while horizontal transhumance is from, for example, river grazing to rainfed grazing on the plains. This classification has been made to better understand pastoralism and is by no means absolute. Some herders practice both types of movement depending on the distribution of rains and floods. An example of vertical transhumance are the Beni 'Amer who descend from the Eritrean highlands in the summer to graze in the Gash Delta; later to return to the mountains in winter. An example of horizontal transhumance are the Fulbe of Mali who leave the Niger Inland Delta in central Mali with their livestock and travel north following the new growth of grass produced by rains associated with the northward summer movement of the Inter-Tropical Convergence Zone.

In Red Sea Province both types of transhumance are practiced. The Red Sea Hills and coastal strip are used for winter grazing and the interior of the province, particularly the southwest corner, are used for summer grazing. There is a vertical movement from coast to mountain to interior and back and a horizontal movement from the Gash Delta to southwest and southcentral Red Sea Province. These movements are dependent on the year. In some years the herds do not leave the GashButana area and in others, like 1988, where thousands of head entered Red Sea Province to utilise the excellent grazing. There is also a delta to delta (coast to plain) movement from the Tokar Delta in June to the Gash Delta. This is called "grazing the two autumns" in Arabic.

Herders also use space to minimise risk in another way. They routinely keep one part of their herd in one place and other parts of it elsewhere. In case of disease, local drought, or raiding they have something to fall back on by employing strategy two, herd splitting.

The third common economic strategy employed by herders is herding different types of livestock. This strategy is useful in maximizing the use of varied pasture and in combatting heavy losses of one breed due to disease. Each type of animal has different grazing and watering requirements and different types of animal are grouped to minimise labour requirements. The most common combination in Red Sea Province are sheep and goats, while in the Gash it is sheep, goats and cattle. In more arid areas of the province camels, sheep and goats are herded. Although goats are more drought resistant than sheep, sheep have a higher market value. In addition, the market value of sheep to cereals appears to be more stable than the value of goats to cereals. Some groups of herders, for example the Rashayda and Nurab, specialise in camels and sheep and shun goats. In general, people raise goats because they have to. Sheep, camels, and cattle are much preferred to goats.

The fourth common herding strategy is mutual aid. Mutual aid in Red Sea Province has two forms according to Hassan Mohammed Salih (1976). The first form is the loan of an animal to a relative so that he or she benefit from the milk. This loan has to be repaid. The second form of mutual aid is the outright gift of an animal or animals to an impoverished relative. This assistance does not have to be repaid. Hassan Mohammed Salih does not mention mutual aid between non-kin among the Beja In this family-oriented society assistance to non-kin may be rare or nonexistent,

The fifth herding strategy are social mechanisms, or institutions based on the redistribution of livestock wealth. This sort of redistribution involves the transfer of livestock between families being united by marriage, the gift of livestock for a birth, coming of age, death, and the payment of livestock as penalty for unlawful conduct. In the precolonial period, the price of murder was paid in camels. This practice has fallen into disuse today, perhaps because camels are no longer as important as they once were before the decline of the caravan trade. Raiding also once was a mechanism for the redistribution of wealth and ecological adaptation (see Sweet 1965).

Social mechanisms of livestock redistribution can play an important role in recovery from livestock loss. For example, the livestock recovery rate of families with several daughters who became marriageable after the drought of 1983-84 in Red Sea Province was good because many livestock are given as a dowry in marriage.

The sixth common strategy practiced by herders is economic diversification. By diversification is meant involvement in activities other than herding of some member or members of the herding family. Agriculture, for an example discussed above. Herders are also periodically involved in the wage labour economy on a seasonal or stress-period basis. Other activities include making charcoal or selling firewood, selling rural products like Duum nuts or the fruit of Ziziphus spina-christi, making mats, blankets, baskets, and leather bags.

Pasture distribution in and around Red Sea Province is presented in the following two maps of Normalized Difference Vegetation Index (NDVI) data. These maps are made from analyzing data on the greenness of vegetation from satellites. The two maps should be examined in conjunction with information from the section discussing Beja groups and migration. Values for the most mountainous parts of the Red Sea Hills are uniformly low because the cell size of the NDVI is 1 km2 and as most of the khors in the hills are less than 1 kilometre in width they are not perceived by the sensors on the satellite. The NDVI index is on a scale of -1 to 1. This represents bare rock to high amounts of vegetation. The NDVI scale was divided into three classes to produce the two maps below: .02-.07, .08-.18, and greater than .18. These classes represent sparse (diagonal hatching), medium (cross hatching), and high (filled) densities respectively. On the map produced from the September-October image the dense vegetation (including agriculture) of the Tokar Delta, Eritrean highlands, the Gash, Gash Dai, Braytek basin and Khor 'Arab basin is clearly visible. Of importance is the distribution of vegetation in the category .02 to .07. This was a result of the high and uniformly distributed rains of 1988. Parts of the province looked like fields of wheat.

The map produced from the NDVI image for March 1989 presents a different story. This is the driest time of the year and only residual grazing- is left. Nevertheless, there remain three areas of high vegetation: parts of the Tokar Delta, parts of the Eritrean highlands, and part of the Gash Delta


Map 1.5. NDVI, September 1 - October A 1988. Red Sea Province.


Map 1.6. ND VI, March 22-24, 1989, Red Sea Province.

 

Drought-coping strategies

People practice a variety of drought-coping strategies in Red Sea Province. Most of these involve intensification of activities they already perform, for example, labour migration. These strategies are characteristic of the early onset of stress. Others strategies employed when stress is acute is migration to urban areas, camps, or the roadside to obtain relief from government and international donors. Cutler (1986) depicted a three-stage sequence of drought coping in Red Sea Province of adaptive strategies, sale of assets, and mass migration. Based on Cutler's work and work of the Research Section of Oxfam Port Sudan, the following sequence of drought-coping strategies can be formulated.

1. Initial response: intensification of activities already occurring in some form. This response stage involves food consumption reduction, the consumption of bush foods, borrowing from kin, storage rather than sale of household cereal production, the increased sale of livestock, new or increased involvement in artisanal production, and greater and longer labour migration. At this level great consideration is paid to such herding strategies as herd splitting and travelling to or remaining in the favoured herding areas such as the Gash or Tokar Deltas, the Nile valley, the Atbara valley, or the Gedarif area rather than risk movement under uncertain prospects for pasture production.

2. Medial response: calling in of loans, the sale of assets such as gold, silver, tools, breeding stock, borrowing from traders.

3. Terminal response: out-migration in search of assistance. Mostly old people, women and children ever employ this strategy in Red Sea Province. By the time conditions get this bad, most men of working age are no longer present. They are with livestock or seeking employment in towns.

The ability to respond to stress is conditioned by a variety of factors. These factors, or variables, interact on the micro and macro levels. The ability to respond at the micro level, the level of the individual or family, is conditioned by the economic and social circumstances of the individual, age, gender, family size, and location. The ability of individuals or families to respond is affected by several trends and processes at the macro level. These trends or processes are the level of development, economic instability, political instability, environmental variation, environmental degradation, and population growth.

 

Population and human geography

Until recent times the population of Red Sea Province has been predominantly rural. Urbanisation can be said to have begun with British administration during the first half of this century although settlements at Suakin and Tokar had developed before that time during the period of Turkish control (al-turkiya). Towns were established for a variety of reasons in the province, most often to service the railway. Over fifty railway towns were built in the early part of this century. Many of these towns have remained insignificant, some have developed into small centres, and a few into towns. Other towns were founded as border posts (Garora), military settlements (Gebeit, Halaib, Muhammed Qul), agricultural settlements (Tokar, Ma'arafiit), smuggling centres, ports for mineral exports (Abu Ramad), and as religious settlements (Hamashkoreb and Tumaala). Today, towns of notable size in Red Sea Province include Derudeb, Garora, Gebeit, Halaib, Haya, Port Sudan, Sinkat, Suakin, Tahamyam, Tokar and the two religious settlements of Hamashkoreb and Tumaala. Other towns of smaller size but still of note are ' Agig, Gebeit al-ma' adiin, Ma' arafiit, Musmar, and Sallum. The following table presents town populations for Red Sea Province.

Table 1.1 Town population of Red Sea Province, various dates.

Town

Population

Date

Gadem Gafrit camp

14400

1988

Garora

11000

1988

Gebeit

7002

1983

Hamashkoreb

15000

1989

Haya

3795

1983

Musmar

2000

1986

Port Sudan Town

273436

1987

Sinkat

7918, 15000

1983, 1989

Tokar

12190

1983

The figures for Gadem Gafrit and Garora in Table 1.1 were obtained from the United Nations High Commission for Refugees (UNHCR). The Hamashkoreb population was estimated by the Environmental Research Group Oxford (ERGO). The Musmar population and the Sinkat population for 1989 were estimated by the Norwegian Red Cross.

Port Sudan, as well as most other centres in the Sudan, has changed considerably in the past 20 years. It has grown in population and has expanded spatially. Maps 1.7 and 1.8 of Port Sudan in 1967 and 1985 illustrate its spatial growth (see James 1969). The size of Port Sudan has doubled since 1967. The bulk of this growth has been in the unplanned settlements, or dayms. The maps below illustrate the growth of Port Sudan as well as the transformation of unplanned to planned settlements.


Map 1.7. Port Sudan In 1967.


Map 1.8. Port Sudan In 1985.

Port Sudan has continued to grow since 1985. Today the dayms have grown and there are new settlements around the town. Appendix 1.2 contains a list of all the dayms in 1989, the settlement dates of recent dayms, and ethnic composition of the dayms

The size of the population of Red Sea Province has always been a subject of speculation. There have been three censuses of the population of the province. The first census was in 1955, the second in 1973 and the last in 1983. Total enumerated population in 1983 was 695854 people. In 1987 there was an update of the census done through the calculation of fertility rates and projecting the 1983 figures forward in time.

Table 1.2. Red Sea Province population by District, 1983 and 1987.

District

1983

 

1987

 
 

Population

%

Population

%

Derudeb

49299

7

59371

7

Halaib

80537

12

96999

12

Haya

42412

6

51008

6

North Tokar

102749

15

123757

15

Port Sudan Town

227968

33

273936

33

Rural Port Sudan

48104

7

57696

7

Sinkat

63072

9

76095

9

South Tokar

81713

12

97835

12

TOTAL

695874

 

836197

 

SOURCE: Department of Statistics 1987 and 1983.

Rural population according to the results of an aerial survey by Watson (1976) in December 1975 was 234259 people. The figure used by Oxfam and the World Food Programme for the allocation of relief food is 400000 rural people. The Environmental Research Group Oxford in an aerial survey done in January 1989 found a rural population of 272000 people (standard error of ±9%). Although these figures provide a rich basis for debate, what is probably more important for most people is the population trend rather than specifics. The following figure illustrates the trend in population growth in Eastern Region since the beginning of this century. Although growth has been great, it should be borne in mind that the population of the Sudan, particularly the central and westerns portions, declined during the last century to an unknown but significant extent because of war, disease, and slavery.


Figure 1.1. Population, Eastern Region of the Sudan, 1900 to 1983.

The Red Sea Province is inhabited principally by the Beja, a Cushitic-speaking group of people that traditionally practiced herding, farming, and trade but now practice a variety of activities many of which involve the urban economy. The Beja are subdivided into five groups', the 'Ababda, the 'Atman (Amarar), the Beni 'Amer, the Bishariin, and the Hadendowa. Minor groups include the Artayga, Ashraf, Halenga, Kumaylaab, Melhitikinaab, Sigulaab, and Shi'ayaab (see Ausenda 1986, Hassan Mohammed Salih 1976, Nadel 1950, Newbold, 1935, Owen 1937, Paul 1954, 1950, Sandars 1933, 1935, and Seligman and Seligman 1930).

Further information about the ethnic groups of Red Sea Province and their seasonal movements can be obtained in ERGO (1989).

With the exception of the 'Ababda and the Beni 'Amer, the Beja speak a common tongue, Tu Bedaawi, although there are identifiable regional differences. The 'Ababda speak Arabic and the Beni 'Amer speak predominantly Tigné. There are questions regarding the inclusion of the 'Ababda and Beni 'Amer with the Beja group. Morton holds that the Beni 'Amer and the 'Ababda should be excluded from the Beja group for ethnic and linguistic reasons. The 'Ababda should not be included for linguistic reasons. He states (1989: 11) that the Beni 'Amer are

... a confederation of tribes, formerly united under a single ruling aristocracy, a system marked by many caste-like practices (Nader 1945, Paul 1950). This system was only abolished in 1948. The aristocracy was Arabic speaking, the vassal groups mainly speakers of Tigré although some spoke Beja. Beni Amer are not now normally considered Beja by themselves, Beja, or others.

Beja society is segmented. Each group claims descent from a common ancestor and traces his or her descent typically four or five generations into the past. For example, for the Hadendowa the common ancestor is Baraakwiin. According to Hassan Mohammed Salih (1976: 38), the Hadendowa social organisation is based on a "... patrilineal genealogical structure which constitutes a segmentary system of sections and subsections." The section, or maximal lineage, is called the 'adaat, and the subsection is called the diwaab. The diwaab vary in size and may be scattered over a wide area.

The most populous of the five Beja groups are the Hadendowa. The 'Ababda are found principally in Egypt, the 'Atman inhabit a broad strip that extends from the Red Sea coast north of Port Sudan and south of Muhamrned Qul to Musmar on Khor 'Arab in central Red Sea Province. The Beni 'Amer are divided between South Tokar District in Red Sea Province, Kassala Province and Eritrea The Bishariin are divided between Red Sea Province, Kassala Province and Egypt. The Hadendowa are split between Red Sea: Province, Kassala Provinces and Eritrea Although a group may be said to be split between two or more areas, it does not mean that there are no links between them. On the contrary, there is much movement across zones and borders in the search for grazing, agriculture, or employment.

The Beja are not the only group that lives in Red Sea Province. Other groups which live there are the Rashayda and Takaariin. The Rashayda are Arabs who began migrating from the Arabian Peninsula about 130 years ago. The migration of the Rashayda, traditional enemies of the House of Sa'ud, increased in the 1920s and 1930s as King 'Abd al 'Aziz consolidated his power over the peninsula and drove out his enemies. The principal occupations of the Rashayda are trade outside the auspices of government regulation and camel herding. The Rashayda have no land rights in the province. They pay land owning Beja for the right to camp and graze their animals. The Takaariin are West Africans who live principally in Tokar and work on the agricultural scheme. They are also found throughout the Sudan principally in areas where agricultural schemes are located. Their ancestors were pilgrims to Mecca who settled permanently in the Sudan (Al-Naqar 1972, Paul 1954, Salih El-Din 1988).

Map 1.9 below presents territories belonging to Beja groups in Red Sea Province. What is immediately evident from the map is that there is a north-south alignment of the territories. This is in fact the general pattern of transhumance for all of the groups living in the Red Sea Province. Most lineage groups possess territory in the north and in the south - in the Gash Delta, along the 'Atbara River, or even on the Nile River. Perhaps the best exemplification of the spread of risk over space in and around Red Sea Province is provided in Hassan Mohammed Salih (1976) in his discussion of the distribution of 'adaat, or maximal lineage section, territory or the Hadendowa Most Hadendowa 'adaat, or as they are increasingly being called, qabiila (plural qabaai°1), possess territory in Red Sea Province as well as in the Gash Delta. Their seasonal movements are, for example, to the north along the Red Sea Hills or coast in the winter and to the Gash Delta or all the way to the 'Atbara River during the summer and fall. Hassan Mohammed Salih (1976) lists 14 Hadendowa maximal lineages and their territories. Ten of the lineages possess territory in Red Sea Province as well as in the Gash or on the 'Atbara River.

In the following discussion of migration patterns, the most northerly of the Beja groups are discussed first. The 'Ababda, principally concentrated in Egypt and not numerically significant in the Red Sea Province, are not discussed. It should be borne in mind that with the exception of well-known cases of ongoing intergroup feuds and land use competition, there are no strict boundaries to land use in or around Red Sea Province; anyone can come and graze his or her animals at any time in any place providing that the rightful owners of the land are recognised and paid a small symbolic tribute. Use rights are completely different from ownership rights in Red Sea Province. Because of the unpredictable amounts and distribution of rainfall, enforcing strict territorial rights in grazing would be a poor survival strategy. This is not to say that this has never been done; in the past there was much intergroup raiding and conflict (see Sweet 1965, Thesiger 1984).


Map 1.9. Beja territories in Red Sea Province.

The Bishariin are divided into two broad groups: the Bishariin Umm 'Aly and the Bishariin Umm Nagy. The territory of the Umm 'aly is situated in the central mountain areas of Halaib District. These are high mountains where precipitation is greater than surrounding areas. The Umm 'Aly move between the coast and mountains in the winter to the Sinkat, Musmar, and Khor Arab and Nile River areas in the summer.

The Bishariin Umm Nagy move longer distances than the Umm 'sly. They graze in the mountains of central and northern Halaib during the winter and move south to the 'Atbara River and west and southwest to the Nile River. Many of the Bishariin who had land use rights along the Nile near Wadi Halfa were given tenancies in the Khashm el-Girba agricultural scheme located on the 'Atbara River southwest of Kassala During the winter rainy season the Bishariin graze their animals along the coast and eastern Red Sea Hills. The Bishariin are also involved in trade with Egypt, principally Aswaan. Morton (1989) found that the principal regional economic centre for the Bishariin Umm Nagy is Aswaan.

The bulk of the 'Atman (Amarar) territory is located in the central Red Sea Hills. During the summer rainy season the Amarar move with their animals to the 'Udrus and 'Arab basins where there is good grazing and cultivable land. During the winter rainy season, the Amarar graze the coast and eastern portions of the mountains which receive rain.

The Hadendowa, the most populous of the Beja groups, move south during the summer rainy season to the Braytek basin, the Gash Dai, the Gash Delta, the Khashm el-Girba scheme on the 'Atbara River, and to the Gedarif area (Abdel Hamid M.A. Bakhit (1988). Sometimes, depending on the distribution of the rainfall they move south into Eritrea During the winter months when the coast receives rainfall the Hadendowa graze their animals from Suakin down to and into Eritrea where they have grazing agreements with the Beni 'Amer.

The Beni 'Amer move in many directions from their mountains. During the summer they move into the Kassala area to graze their animals and to pursue other activities in the agricultural schemes. In the winter rainfall season there are two movements: one group of Beni 'Amer moves down to the Tokar Delta for grazing and agricultural labour and another group of more pastoral Beni 'Amer remains in the mountains or descends to the Eritrean coastal areas if grazing is abundant.

There are two groups of Rashayda that use pasture in Red Sea Province. The first group migrates from the Tokar delta in May-June along Khor Baraka to the Kassala area where higher and earlier precipitation makes good general grazing outside the khors. The Rashayda move to the 'Atbara River and into the Butana Plain. Sometimes, when conditions warrant, they will move all the way into Eritrea. Another group of Rashayda migrate to Egypt from Halaib District's coastal area in the winter. This group migrates down to the 'Atbara area in the summer.

The relations between the 'Ababda, 'Atman, Beni 'Amer, Bishariin, Hadendowa, and Rashayda have in the past been hostile and are today sometimes tense. The major source of conflict in the past and at present are land rights and land use. These groups may be said to exist in a state of competition for scarce resources. The following table, taken from Hassan Mohammed Salih (1976: 135) illustrates the nature of the competition for scarce resources.

Table 1.3. Cases of animal thefts, injuries and homicide among the Hadendowa In the Gash Delta, 1969-70.

Month

Animal Theft

Minor Injury

Major Injury

Attempted Homicide

Homicide

June

145

114

34

2

8

July

27

32

3

1

0

August

36

42

6

1

0

September

69

43

6

1

2

October

104

47

17

2

5

November

68

54

8

1

4

December

67

63

12

1

4

January

58

63

19

0

4

February

50

53

26

0

4

March

91

45

30

1

5

April

58

65

31

2

5

May

116

115

30

2

7

Two points emerge from the table: the conflicts are seasonal and they are violent. The lowest months for murder and all other conflict, excepting attempted homicide, are the months of July and August, periods of plentiful fresh pasture production by floods and rain. The worst periods are those leading up to the new flood and rain year the driest season of the year, when available grazing and browse is at its lowest level.

 

Land Tenure

Land is held by the maximal lineage, 'adaat. Two rights in land ate observed: a'amara and asl rights. A'amara fights are usufruct rights of land for pasture, agriculture, and other activities such as cutting wood and imply no ownership of the land. A payment, called gwadaab is made annually to the diwaab that possesses full ownership rights of the land being used. This payment, sometimes only nominal, may be in animals or grain.

Asl rights, in contrast, are full ownership rights. Individuals and families have the right to maintain possession over particular plots of land for as long as they use them. Their descendants have the right to use the same parcels. Only asl possessors have the tight to sink or repair wells or to cut trees.

Land use arrangements for agriculture such as sharecropping exist in Red Sea Province and the rules governing such arrangements are more complicated than those governing pastoral land use between a'amara and asl tenure holders. There are three levels of sharing in general: landowners, half sharers, and quarter sharers. These levels are called in Arabic saahib adh-dhimin (saahib al-hawaasha or saahib al-arch), saahib an-nuus, and saahib ar-ruba' respectively. The landowner in theory takes one-half of the products of the land and the half sharer takes the other half. In practice this can vary considerably. The half sharer is responsible for hiring of labour and the payment of labour in kind or, less commonly, in cash. A sharecropping system such as the one described can exist where land is "collectively" owned by the maximal lineage because the minimal lineages, diwaabs have established customary rights of usage over specific parcels of land. These rights are inheritable. Land may be let as well.

In the precolonial period rights to land in Red Sea Province were established by conquest and maintenance of those rights involved war. Insofar as the land ownership status quo before the British established their administration in the early part of this century can be considered traditional land ownership and violence accepted as a means of negotiation, we may say that land ownership has changed since the precolonial times. Traditional land rights in Eastern Region have changed as a result of policy decisions made by the colonial administration and the independent central government in recent times. In the Tokar Delta in the early part of this century land was given to individuals who could clear it of trees and scrub and cultivate it. Large tracts of land passed (peacefully) to local people who previously had no asl rights to the land and some land passed to outsiders. In the development of the Gash Delta beginning in the early 1920s, in contrast, land remained in the hands of the local people who themselves had seized it violently from others a century before.

The central government in Khartoum has legislated that all land belongs to the state. This has been contested in the Eastern Region. Further information on this subject may be found in the forthcoming graduate theses from the Red Sea Areas Programme of the Universities of Khartoum and Bergen.

 

Gender Relations in Beja society

There is a clear sexual division of labour in Beja society and it may be said that gender is one of the most important issues in Beja life. The table below presents the sexual division of labour of rural Beja people in Red Sea Province.

Table 1.4. Traditional sexual division of labour In Red Sea Province.

Task

Performer

 

Men

Women

Basket making

 

X

Wool blanket weaving

 

X

Charcoal making

X

 

Domestic chores*

 

X

Erecting tent

 

X

Fetching water*

X

X

Food preparation

 

X

Fuelwood collection*

 

X

Harvesting cereals

X

X

Harvesting cotton

 

X

Herding camels

X

 

Herding goats**

X

 

Herding sheep**

X

 

Labour in Gash

X

 

Labour in Tokar

X

 

Leather bag making

 

X

Marketing

X

 

Mat making

 

X

Milking livestock

X

 

Planting cereals

X

X

Raising chickens

 

X

Rope making

X

X

Temporary shelter construction

X

 

Trade

X

 

Wage labour in Port Sudan

X

 

* Also performed by children around the tent.

** Performed by women around the tent with the milk herd.

In addition to the sexual division of labour there is a strict division of between public and private life that is based on gender. Women's roles are private and domestic while men's are public. As in many traditional societies, the Beja women's role is principally related to food preparation, homemaking, and reproduction. Women's roles are totally rural and home oriented while, men enjoy a mix of rural and urban activities.

Although women do own property in animals, they are not allowed to milk them and their ownership has to be seen in context. If an animal needs milking, even if it is her own, she must call a male relative to come and milk it for her. Women accumulate assets in livestock and jewellery earned from a variety of economic activities depending on location, however, women are dependent on their husbands or male relatives to market all goods and crafts they produce. Although shar'iyya law stipulates that women should inherit one-half the share of her brothers, women generally cede al} their rights of inheritance to their brothers. An exception to this is the inheritance of the tent and the implements belonging to the tent. These are passed down from woman to woman. Adobe and wooden houses, in contrast, are built and belong to men and form part of their inheritance.

The woman's domain is rural and she rarely in her lifetime visits the towns of Red Sea Province; it is the man's role to act as the interface with the outside world. The practical implication of this system is that men, entitled to be public creatures, obtain the benefits of the towns and women and their children do not. An example of the implications of the dichotomy between the public world of men and the private world of women is the more varied and nutritious diet of men who eat in roadside restaurants and in Port Sudan where lentils, beans, meat and other nutritious foods are available at little cost. In normal times, however, rural women are poorly nourished (Anonymous 1968) and in times of drought or economic inflation the food stress problem is critical. The irony is that women's nutritional needs during their reproductive years are greater than those of men.

Education for women is viewed by rural people as sinful and dangerous because it leads to public life and dishonour. Town dwellers normally only educate their daughters, if they educate them at all, to primary level. There is much social pressure against the father who wants to educate his daughters above the primary level. It is commonly believed that women will become uncontrollable and dishonour the family if they are educated. Traditionally, women are not permitted to enter the market in the town of Sinkat, one of the most conservative areas. Destitute women forced from the rural areas into the periphery of Sinkat by drought and the breakdown of their families sell mats and other goods along the road several hundred metres from the men's roadside service centre and a kilometre from the market. In urban areas women go about veiled and they travel in pairs to ensure each other's honour and presumably to act as witness to the conduct of the other. In areas of comparable conservatism women are sometimes killed because they were believed to have brought shame upon their families by their conduct (see Antoun 1968, Al-Sada'awi 1982).

Women are excluded from political affairs in Beja culture. For example, women were forbidden to go to vote in the last election for the National Assembly (Mohammed Osman Omer 1989). The reasons advanced for such action were:

1. Women's duty is to reproduce and rear children.

2. Women have no understanding about public affairs.

3. It is sinful for women to be with men in public.

The historical basis for Beja gender relations may be related to extreme resource scarcity and the property relations that have developed over time under such conditions of scarcity in Red Sea Province. Fear of alienation of land from the kin group (loss of control) goes far in explaining the genesis and development of gender relations in Beja culture.

To understand the Beja system it is useful to first consider the reproduction of the family, the control over the reproduction of the family, and the control of scarce resources. There are two methods of controlling individuals: social and physical. In general, social controls extend from internal controls developed during socialisation, to mild sanction, to ostracism. Physical controls extend from mild punishment, to irnprisonment, to amputation (in cases involving theft under shar'iyya law), to execution. Control of resources involves restrictions on use and access and sometimes physical presence. En earlier times it required violence. Control over the reproduction of the family is similar to control of resources in that it involves restrictions on use and access.

The Beja system minimises the contact of the female with all outside males who possibly could have a sexual interest in her and who could interfere with the preferred first cousin marriage. The purpose of this practice in the highly competitive Beja tribal society is to minimise land claims and keep the little agricultural land and meagre pasture with the smallest and most closely related familial unit (see Hassan Mohammed Salih 1976, and Abdel Hamid forthcoming).

The family unit is not without competition and conflict. Control of resources within the family and even the composition of the family unit itself is a gender issue. Basically, the family is divided into two groups: the herding unit and the tent cluster (Hassan Mohammed Salih 1976).

The herding unit, a cooperative, patrilineally segmented unit of production designed to overcome labour constraints is composed of one of three groups of men.

1. The household head and his married sons.

2. Brothers and their married sons.

3. A man and his brother's sons.

This group may not have collective rights to the herd but may be instead an "anticipatory inheritance group" (Hassan Mohammed Salih 1976). Brothers will usually keep their herds together unless one of them is particularly industrious, in which case he keeps his animals separately and hires herders.

The tent cluster, in contrast, is composed of females of the family. It is a cooperative group for female tasks. The tent cluster is made up of the mother's tent and the tents of her married daughters and/or sisters with their husbands. The tent cluster expands as its daughter's get married and begins to dissolve after the last daughter's marriage. The reason for this is that at marriage the rules of residence are uxorilocal; this means that the new husband resides at his wife's residence. Control of livestock and livestock products expands with the marriage of daughters as bridewealth is brought to the tent cluster by the sons-in-law. Later, when the daughter's daughters are ready for marriage, she moves her tent away from her mother's tent in order to establish a new tent cluster of the diwaab. This move away from the family is accomplished in this resource-scarce society through the gaining of bridewealth for her daughters. Bridewealth is normally in animals and has the potential to represent for a family the most significant contribution to the family members' lifelong food security. Ownership of animals, however, is not the ultimate arbiter of food security in Beja life. Control of animals, use of the bridewealth, is more important. This is because there is an inherent conflict of interest and competition over the control of animals between the herding unit and the tent cluster. This competition is at the household level between the patrilineal family and the tent cluster that a man joins after marriage. The woman's family attempt to increase the resource transfer (bridewealth) from the son-in-law's family as much as possible while at the same time, the male siblings of the prospective son-in-law attempt to minimise it as far as possible in order to enhance their command over bridewealth for their own marriages. Ultimately, conflict is avoided through the use of first cousin marriage which maintains close relations and minimises the alienation of animals.

An alternative explanation of the Beja system of resource use is resource spreading in a resource scarce environment. Divested of its competition and conflict the Beja system may be explained as a strategy or mechanism, although this explanation is not complete. The herding unit/tent cluster dichotomy, however, may be what remains in this isolated corner of the world of a once-prevalent matriarchy which was replaced by a patriarchal system, later codified in Christianity and Islam. Morton (1989), however, presents a convincing argument against the existence of a matriarchy in ancient times. This matter deserves further investigation.

 

Overview of famine relief in Red Sea Province

In 1985, a World Food Programme famine relief programme began in Red Sea Province. The initial rationale for the programme was to improve the malnutrition rates in the province. When the WFP, feeling that the programme had achieved its objectives, indicated that they were ready to withdraw from the programme in late 1986, Oxfam, feeling that food aid was still needed in the province, advanced the concept of general pastoral economic recovery, or Food for Recovery. The thinking was that the relief food would act as a boost to recovery at different levels of economic life in the province. In this view the relief food contributed to the economy in the following ways.

1. It was used as livestock feed and saved many herds from starvation during the dry season.

2. Grain, sugar, and oil were sold for cash. This had a doubly beneficial effect because it provided ready cash for household needs and also enabled people undergoing economic stress to retain breeding stock which they probably would have had to sell without the WFP commodities.

There was a multiplier effect related to the sale of the foodstuffs on several levels of value-adding exchange based on the input of a free good: from the food aid recipient, to the town based merchant, to the end user. Much of the relief grain and, in particular, oil and sugar distributed in the southern half of Red Sea Province as part of the World Food Programme's relief food assistance has been sold through a valueadding network to Eritrea although no precise figures are available. According to reports in early 1989, a fifty pound sack of sugar is sold for from £400.00 to £600.00 Sudanese in Red Sea Province. same sack is resold at the Eritrean border for over £2000.00 Sudanese.

The average family ration per day was two kilograms of sorghum (sometimes wheat) and quantities of sugar and oil were also provided. The object of the relief effort we. the entire rural population of Red Sea Province at that time who were judged to be at risk. Just over 400 delivery points, or 1 for every 1000 persons, located armed the province were created as points where designated representatives of the estimated 400000 rural dwellers could receive the commodities allocated to their area The programme continued unchanged until 1989 when areas deemed recovered were gradually cut from the relief rolls. There weary, however, two exceptions to this: the Arba'at and Suakin areas were cut in 1988. Arba'at is an area of market-oriented agriculture associated with Khor Arba'at and Arba'at delta and Suakin is a town. It is projected that the relief effort will be terminated by the end of 1989, however, there is some discussion by the World Food Programme about continuing free food deliveries, food for work, and vulnerable group feeding.

 

References

Abdal Hamid M.A. Bakhit. (1988) The highland Hadendowa and their recent migration. In Ibrahim, F. and Rupert, H. (eds.) (1988) Rural-urban migration and identity change. Case studies from the Sudan. Bayreuther Geowissenschaftliche Arbeiten. Volume 4. Bayreuth.

Abdel-Hamid Mohamed Osman Abdel-Rahim. (forthcoming) Land tenure among the Hadendowa of the Red Sea Hills. Red Sea Areas Programme, University of Khartoum, Khartoum.

Alawia Abdalla El-Awad. (forthcoming) Vegetation in the Red Sea Hills. Red Sea Areas Programme, University of Khartoum, Khartoum.

Amal Hassan Fadlalla. (forthcoming) The impact of drought on Beja women. Red Sea Areas Programme, University of Khartoum, Khartoum.

Anonymous (1968) A thesis on the Hadendowa. Department of Anthropology, University of Cairo. Translated from the German.

Antoun, R. (1968) On the modesty of Arab women in Arab Muslim villages: a study in the accommodation of traditions. American Anthropologist, 70: 671-697.

Al-Naqar, U. (1972) The pilgrimage tradition in West Africa University of Khartoum Press, Khartoum.

Al-Sada'awi, N. (1982) The hidden face of Eve. Zed Press, London.

Ausenda, G. (1987) Leisurely nomads: the Hadendowa (Beja) of the Gash Delta and their transition to sedentary village life. Unpublished Ph.D thesis, Department of Anthropology, Columbia University, New York.

Blomberg, Y. and Alstad, G. (forthcoming) Landscape ecology and vegetation history in the Red Sea Area, Sudan. Red Sea Areas Programme, University of Bergen, Bergen.

Bloss, J.F.E. (1937) The story of Suakin. Sudan Notes and Records, 20: 271-280.

Christensen, A. (forthcoming) Fuelwood production. Red Sea Areas Programme, University of Bergen, Bergen.

Cole, M.L. (1988) An evaluation of the impact of the Joint Nutritional Support Programme supported training programmes in education, social welfare, and horticulture in Red Sea Province. UNICEF/JNSP Internal Document, October 1988. Port Sudan.

Cole, R. (1982) The sedentarization of pastoral nomads: an examination of twentytwo settlement schemes. Unpublished MSc. thesis, Department of Resource Development, College of Agriculture and Natural Resources, Michigan State University, East Lansing, Michigan.

Cutler, P. (1986) The response to drought of Beja famine refugees in Sudan. Disasters, 10(3).

Environmental Research Group Oxford (1989) Integrated livestock surveys of Red Sea Province, Sudan. Preliminary report of Phase One aerial and ground survey, February - April 1989. Environmental Research Group Oxford, Oxford.

Fleming, G.J (1920) Tokar. Sudan Notes and Records, 3: 12-23.

Hassan Mohammed SaIih. (1976) The Hadendowa: pastoralism and problems of sedentarization. Unpublished Ph.D thesis, Department of Anthropology, University of Hull, Hull.

James, W.R. (1969) Port Sudan's overspill. Sudan Society, 4: 5-26.

Kassas, M. (}956) The mist oasis of Erkowit, Sudan. Journal of Ecology, 44: 180194.

Lewis, B.A. (1962) Deim El Arab and the Beja stevedores of Port Sudan. Sudan Notes and Records, 43: 16-49.

McLoughlin, P. (1966) Labour market conditions and wages in the Gash and Tokar Deltas, 1900 to 1955. Sudan Notes and Records, 47: 111-126.

McLoughlin, P. (1965) The Gash-Tokar economic region: some aspects of its labour force and income. Sudan Notes and Records, 46: 67-83.

Milne, J. (1974) The impact of labour migration on the Amarar in Port Sudan, Sudan Notes and Records, 55: 70-87.

Mohammed Osman Omer (1989) The impact of drought on the demographic structure of three Eastern Sudanese settlements. In Red Sea Areas Programme (RESAP) (1989) Proceedings from a workshop held in Khartoum, January 1989. The Universities of Khartoum and Bergen, Khartoum.

Morton J. (1989) Descent, reciprocity, and inequality among the northern Beja. Unpublished Ph.D dissertation, Department of Sociology, University of Hull, England.

Nadel, S.F. (1945) Notes on Beni Amer society. Sudan Notes and Records, 26(1): 5194.

Notoy, I. (forthcoming) Land rights systems in the Red Sea Hills and their compatibility with a sustainable development.

Omer Abdalla M. Egemi. (forthcoming) Assessment of resource use and management activities in arid lands and reflections on the human and natural environments: a study from the Red Sea Region of Eastern Sudan. Red Sea Areas Programme, University of Khartoum, Khartoum.

Omyma Said Ahmed Gutbi. (forthcoming) Dockers of Port Sudan. Prom pastoralists to urban workers. Red Sea Areas Programme, University of Khartoum, Bergen.

Owen, T.R.H. (1937) The Hadendowa. Sudan Notes and Records, 20: 83-108.

Paul, A. (1954) A history of the Beja tribes of the Sudan. Cambridge University Press, Cambridge.

Paul, A. (1950) Notes on the Beni Amer. Sudan Notes and Records, 31: 222-245.

Red Sea Areas Programme (RESAP) (1989) Proceedings from a workshop in Khartoum, January 1989. The Universities of Khartoum and Bergen, Khartoum.

Roden, D. (1970) The twentieth century decline of Suakin. Sudan Notes and Records, 51: 1-22.

Salih El-Din El-Shazali Ibrahim (1988) The emergence and expansion of the urban wage-labour market in colonial Khartoum. In Barnett, T. and Abdelkarim, A. (eds.) Sudan: state, capital, and transformation. Papers presented at a seminar held in the School of Development Studies, University of East Anglia, Norwich, July 1984. Croom Helm, Beckenham.

Sandars, G.E.R. (1935) The Amarar. Sudan Notes and Records, 18(2): 195-219.

Sandars, G.E.R. (1933) The Bisharin. Sudan Notes and Records, 16(2): 119-149.

Seligman, C.G. and Seligman, Z. (1930) Note on the history and present condition of the Beni Amer (Southem Beja). Sudan Notes and Records, 13: 83-97.

Sweet, L. (1965) Camel raiding of North Arabia Bedouin: a mechanism of ecological adaptation. American Anthropologist, 67.

Tokar Delta Board (various dates) Annual reports. Tokar Delta Corporation, Tokar.

Vagenes, V. (forthcoming) Red Sea District women in processes of marginalization. Red Sea Areas Programme, University of Bergen, Bergen.

Vetaas, Ole Reidar. (forthcoming) Biotic and abiotic factors in the secondary succession in Erkowit, Red Sea Province. Red Sea Areas Programme, University of Bergen.

Watson, R.M., Tippett, C.I., Rizk, F. (1975) Sudan national livestock census and resource inventory. Volume 15, the results of an aerial census of resources in Red Sea Province in December 1975. Sudan Veterinary Research Administration, Ministry of Agriculture, Food and Natural Resources, Khartoum.

Widstrand, K. (1975) The rationale of the nomad economy. Ambio, 33.

 

Appendix 1.1.

Other current research in Red Sea Province

This section is a summary of the current research undertaken by the Environmental Research Group Oxford (ERGO), and research in preparation or currently under way by the Universities of Khartoum and Bergen collectively called the Red Sea Areas Programmed (RESAP). The ERGO research is presented first abstracts of the RESAP research follow. More detailed information about the research is available in ERGO (1989) and RESAP (1989).

Environmental Research Group Oxford (ERGO)

The Environmental Research Group Oxford was commissioned in 1988 by Oxfam United Kingdom to conduct a two-season aerial survey of livestock, human population, vegetation and agriculture in Red Sea Province and in adjacent areas that are used heavily by residents of Red Sea Province. At present, only a preliminary report of phase one of the survey has been prepared It is envisioned that the final report will be finished in December 1989.

Red Sea Areas Programme Research (RESAP)

Eleven Masters and Ph.D students are involved in the RESAP programme. The research topics are listed first and then a brief description of each topic is presented at the end of the list.

Assessment of resource use and management activities in arid lands and reflections on the human and natural environments: a study from the Red Sea Region of Eastern Sudan. Omer Abdalla M. Egemi.

Biotic and abiotic factors in the secondary succession in Erkowit, Red Sea Province. Ole Reidar Vetaas.

Dockers of Port Sudan. From pastoralists to urban workers. Omyma Said Ahmed Gutbi.

Land rights systems in the Red Sea Hills and their compatibility with a sustainable development in the area Ingunn Notoy.

Landscape ecology and vegetation history in the Red Sea Area, Sudan. Ylva Blomberg and Gunnar Alstad.

Land tenure among the Hadendowa of the Red Sea Hills. Abdel-Hamid Mohamed Osman Abdel-Rahim.

Red Sea District women in processes of marginalization. Vibeke Vagenes.

The impact of drought on Beja women. Amal Hassan Fadlalla.

The impact of drought on the demographic structure of three Eastern Sudanese settlements. Mohammed Osman Omer.

Commercial fuelwood production. Anne Christensen.

Vegetation in the Red Sea Hills. Alawia Abdalla El-Awad.

Biotic and abiotic factors in the secondary succession in Erkowit, Red Sea Province. Ole Reidar Vetaas.

The purpose of this research is to determine whether secondary succession vegetation in the Erkowit area will continue to degrade or reach an equilibrium. TO do this the author uses work done by Kassas in the 1950s in the Erkowit area for a comparative study. Three stages in the author's research must be accomplished to realize the main research purpose: quantify the change in floristic composition from 1953 to the present, analyze the physical and chemical qualities of the soil, and quantify moisture accumulation under tree canopies. Preliminary findings of this research are that there have been significant changes in the vegetation (particularly the trees) in the Erkowit area since 1953. The principal factor identified as responsible for the changes is human land use: tree harvesting for fuelwood, charcoal or other uses and grazing.

Botanical research Babiker Fadlalla

The purpose of this research is to augment our understanding of vegetation and vegetation change in the Erkowit area. The study has the following objectives.

1. To collect plant material for identification.

2. To identify and map natural vegetation.

3. To compare present vegetation maps with those made in the past.

4. To photograph the natural vegetation and the different ecological zones.

5. To produce descriptions and illustrations of the vegetation.

6. To examine several possible causal factors that may be responsible for the distribution and type of natural vegetation. For example, altitude, temperature, atmospheric humidity, rainfall, wind direction and human activities such as fuelwood production and pastoralism.

7. To measure the seasonal change frequency of occurrence and density of ground cover and forage composition.

8. To study the life cycle of grazing species.

9. To collect seeds for experiments under controlled conditions in the greenhouse.

10. To investigate local cultivated crops and fodders and to submit them to chemical analysis to determine their nutritive value.

11. To collect soil samples for chemical analysis and greenhouse experiments.

12. To estimate the seasonal yield in dry matter of the main pasture plants and to determine from this carrying capacity.

13. To examine the possibilities for the introduction of exotic plant species.

14. To examine the human-environment relationship in the study area This includes vegetation use and annual transhumance.

The impact of drought on the demographic structure of three Eastern Sudanese settlements. Mohammed Osman Omer.

Three settlements in the Sinkat area were selected to examine drought and family structure. The author has identified three factors which relate to the impact of drought and the degree of change in family structure. These factors are:

1. The Environment and location.

2. Diversification of the economy.

3. Occupational linkage to urban areas.

The impact of drought on Beja women. Amal Hassan Fadlalla.

This study uses life histories of female migrants to Sinkat in reconstructing the lives of these women prior to the drought and making the comparison with their present circumstances. This work is in its early stages and results are forthcoming.

Dockers of Port Sudan. From pastoralists to urban workers. Omyma Said Ahmed Gutbi.

In this study dockworkers in the Port Sudan port were interviewed using questionnaires and informal techniques. Preliminary findings indicate that droughtinduced impoverishment in the rural areas has increased migration to Port Sudan dramatically. People are increasingly replacing seasonal migration to Port Sudan with permanent settlement.

Assessment of resource use and management activities in and lands and reflections on the human and natural environments: a study from the Red Sea Region of Eastern Sudan. Omer Abdalla M. Egemi.

The purpose of this research is to study the use of natural resources in Red Sea Province, to evaluate present development activities in the Province, and to investigate the social and cultural factors that influence the use and management of natural resources.

The author hypothesizes that:

1. Resource degradation did not suddenly occur in the early 1980s as a consequence of drought. Instead, it is the result of a long process of degradation.

2. Successful development builds and improves on what people are already doing.

3. The traditional territorial system in the area is a major barrier to development.

4. Relief food offers no long-term hope for the area and instead may form an obstacle to efficient management and development.

Land tenure among the Hadendowa of the Red Sea Hills. Abdel-Hamid Mohamed Osman Abdel-Rabim.

The purpose of this study is to describe the Hadendowa land tenure system. The following topics provide the focus for the research.

1. The evolution of the Hadendowa customary land use law.

2. The system used by the Hadendowa to manage land-use conflict.

3. Continuity and change in the land tenure system and the role of local, regional and national institutions.

4. The appropriateness of the Hadendowa land tenure system in development planning.

This study is in its preliminary stages and no results have been made available to date.

Vegetation in the Red Sea Hills. Alawia Abdalla ElAwad.

This study is in its preliminary stages and no results have been made available to date, however, the purpose of this study is to:

1. Obtain a reference collection of the flora of Red Sea Province for the herbarium in Khartoum.

2. Examine and map the distribution of vegetation types using aerial photographs and satellite images.

3. Identify plant species to serve as indicators of environmental change.

4. Document the status of post-drought vegetation in Red Sea Province.

Commercial fuelwood production. Anne Christensen.

In this study the impact of Port Sudan demand on charcoal production in Red Sea Province is examined. Areas studied include Khor Dahant, Khor Agwamt, Khor Udrus, and the coastal plain. This study is in its preliminary stages and no results are as yet available.

Land rights systems in the Red Sea Hills and their compatibility with a sustainable development in the area Ingunn Notoy.

In this study the impact of the national government on traditional land ownership. In the precolonial and colonial periods, tribal shaykhs were responsible for land allocation and the resolution of land disputes. In 1970 the Unregistered Land Act was passed. This Act stipulated that all land not registered belonged to the national government. In 1971 the Local Government Act was adopted by the Sudanese government. This Act removed the power of tribal shaykhs to allocate land and adjudicate ownership disputes. This power was given instead to civil servants at the District Council and Village Council levels.

Red Sea District women in processes of marginalization. Vibeke VÃ¥genes.

The purpose of this research is to describe the current and past status of women in Red Sea Province with particular emphasis on their involvement in the market. Three areas are to be examined in the study:

1. Women in the traditional female structure.

2. Women in the female-headed household.

3. Women involved in the Sinkat Centres for Women.

There are as yet no results from this research.

Landscape ecology and vegetation history in the Red Sea Area, Sudan. Ylva Blomberg and Gunnar Alstad.

The focus of this research is on the quantitative study of the present vegetation of Red Sea Province, vegetation history and soil analysis. LandSat data, aerial photographs, and ground data will be used in the study. The study is in its preliminary stages and no results have been made available to date.

 

Appendix 1.2.

Port Sudan 1989, class of housing, settlement dates of unplanned areas, and ethnic composition.

NAME OF AREA DATE

GROUPS

   

Housing quality 1: Cement block flats

 

Hai al-'azhima

Northerners, Yemenis

Tranzayt

Foreigners, Yemenis

Hai al-mataar

Northerners

Daym al-shaty

Yemenis

   

Housing quality 2: Principally cement block flats

 

Daym al-madiina

Northerners

Tarab hadal

Northerners

Al-thawra

Eritreans

Al-askiila

Northerners

   

Housing quality 3: Wood construction

 

Sala lab

Northerners , Beja , Eritreans

Daym al-'arab

Beja

Sikka al-hadlid

Northerners

Al-marghaniya

Eritreans, Beja

Daym al-nuur

Northerners, Beja, Beni 'Amer, Eritreans

Daym kuriya

Northerners, Kordofanians

Abu hashiish

Northerners

Salabuna

Northerners

Daym al-takaariin

West Africans

Daym muusa

West Africans

Daym jaabir

West Africans

Daym mayu

Nubians, Beni 'Amer

   

Housing quality 4: Shanty

 

Daym al-wuhda

'Atman, Beni 'Amer

(fringe areas 1983-84)

 

Daar al-salaam (1975-76)

Beni 'Amer

Daar al-na'im (1983-84)

Tokar people, Beni 'Amer

Ongwob

'Atman, Beja

Hai phillip

Nubians

Hai walk (1984)

Beja

Salalab shanty

'Atman, Hadendowa

Ras al-shaytaan

Ethiopians

Daym al-ramla (N Daym muusa)

Eritreans

Barcelona (SW Daym al-nuur)

Eritreans

 

 

2. Measuring drought and food insecurity in Red Sea province: in 1987 and 1988: a technique for Pthe rapid assessment of large areas. Roy Cole

 

Summary

A system of rapid areal assessment of drought impacts and food insecurity was developed in Oxfam Port Sudan for use in 1987 and 1988. The system was designed to be used in the absence of sophisticated technology such as satellite imagery and extensive quantitative data. Experienced field workers used six variables related to drought and economy to assess the impact of drought and food insecurity in the province. Results indicate that the greatest drought impacts and food insecurity in 1987 were in the southwestern interior of Red Sea Province and in the South Tokar coast. The former area is one where the floods failed for two consecutive years, 1983 and 1984, and where destitute people moved to the roadside in 1985 to beg for food. The latter area is a destination of war refugees from Eritrea and people trapped by the war in Red Sea Province and prevented from pursuing their normal patterns of transhumance from the Red Sea lowlands to the Eritrean highlands. Low drought impacts and food insecurity scores appear to be linked with relatively reliable agriculture such as that practiced in the Tokar Delta or linkage to an urban area. The unprecedented rainfall of 1988 was felt principally in the southern and central parts of the province according to the evaluation. The northern areas stayed the same or declined.

The results of this study indicate that drought and drought risk must be reexamined in Red Sea Province. Two things must be looked at: the potential for change in an area (interannual variability) and the existence of intervening, exogenous variables (for example, war) that affect the ability of people to respond to drought and economic adversity. Where environmental variability has historically been greatest we found the worst and the best results from year to year. However, for those areas that remained the same during both periods, we found a relative lack of potential for improvement. Locusts had an important impact on the scores only in the southwest of the province and southwest of Suakin in 1988.

The technique could be improved if the following conditions are met:

1. The unit of analysis should be smaller.

2. More variables should be included.

3. To minimise differences in observers only one person should do the classification.

 

Introduction

In early 1988 the Research Section at Oxfam Port Sudan developed a system for rapid areal assessment for relief food allocations for the Oxfam Food Monitors. The assessment system was part of some early explorations into changes of the Food Monitoring procedures and was also intended to provide information about drought impacts and food insecurity for 1987. The intention was to provide a spatial unit and structure for the Oxfam Food Monitoring Team's evaluations of areas for relief food allocations as well as criteria for a more systematic and accountable evaluation than had been done previously. The work was repeated at the end of 1988 to provide additional data for comparison.

 

Methods

Experienced field workers were asked to rank on six variables each of the subecozones ("strata") defined by Watson (1976) in his study of livestock and human population in Red Sea Province. Some of the field workers had been involved for the three previous years in touring the districts of the province making relief food allocation assessments and others touring for nutritional assessment of children under five years of age. Assessments of the zones for the purposes of the present study were done while assessments for relief food or nutritional surveillance were being made. The assessments were not done at one moment in time but reflect repeated visits and are a composite of the conditions prevailing in or around each zone throughout each year of study.

Watson's subecozones are a subset of his ecozones ("ecotypes") which were defined from satellite imagery and ground observation using variables relating to vegetation, geomorphology, soils, drainage, and topography and fall into the classes presented in the following table.

Table 2.1. Ecozones used In Watson (1976).

Ecozone

Name

Area

Number

(km2)

 

1

Coast

20896

2

Mountain

66276

3

Interior

112412

4

Khor 'Arab watershed

12611

5

Khor Baraka and Osir watersheds

4624

6

Tokar Delta

1136

 

TOTAL AREA

217955

Watson's 25 subecozones were used as the basis for the present study. They were slightly altered for the 1987 data and changed considerably for the 1988 work This was done because Watson based his classification on physical features of Red Sea Province. Our purposes involved people in addition to the environment. Zones were altered, for example, to reflect tribal territory, migration patterns, or the presence of significant towns. Watson's strata may be grouped into the following classes.

1. Coastal strip units.

2. Contiguous mountain units.

3. Watershed units.

The map on the next page presents the ecozones and subecozones of Watson.


Map 2.1. Ecozones and subecozones used by Watson (1976).

The six variables to classify each of the subecozones thereafter called "zones") far the present study are as follows:

1. Rainfall quantity and distribution.

2. Abundance and condition of useful vegetation.

3. The cash crop harvest.

4. The food crop harvest.

5. Livestock numbers, condition and recovery from drought.

6. The availability and use by zone residents of economic opportunities in or outside their zone.

The first two of these variables were used to measure drought impacts and the four remaining variables to measure food (and economic) insecurity. The scores for each variable were scaled from 0 to 3: None, Poor, Medium, and Good. The responses for each group of variables were summed (1 and 2 equals "Drought Impacts", 3-6 equals "Food Insecurity") and were plotted with Food Insecurity on the Y axis and Drought Impacts on the X axis.

The data were grouped into four classes according to the deviation of each zone from the mean for each year. Group 1 is equivalent to low drought impacts and food insecurity. Groups 2 and 3 are equivalent to moderate drought impacts and food insecurity; group 2 being moderately above and group 3 being moderately below the mean. Group four is equivalent to high drought impacts and food insecurity. These classes break down in standard deviations from the mean as follows (see Maps 2.2 and 2.3 also).

1. Greater than 1 standard deviation above the mean.

2. Zero to 1 standard deviation above the mean.

3. Less than 0 to 1 standard deviation below the mean.

4. Greater than 1 standard deviation below the mean.

Although it is useful to use means and standard deviations in interpreting the within years scores, it is more informative to use raw scores to compare the change from one year to another. This method gives results for each zone uninfluenced by the scores of the other zones for that year. What is of interest in this case is the performance of the zone from time 1 to time 2 not the relation of the zone to the other zones at time n. A technique for the standardization of unlike spatial units was employed to accomplish the comparison of each zone with itself over the two time periods. A grid composed of cells sized one-half the area of the smallest zone on the maps of Drought Impacts and Food Insecurity was superimposed over each map. For all areas that had a value for both years a difference was calculated and placed in the common grid cell. These cells were then grouped and mapped. The range of classes used in the grouping and mapping are as detailed below. The values reflect the number of positive or negative points change for the cell from 1987 to 1988.

1. >= 5 points change.

2. 2 - 4 points change.

3. 1 to -1 points change.

4. -2 to -4 points change.

5. <= -5 points change.

 

Results

Average scores and standard deviations for 1987 and 1988 are presented in the table below. The scores for each assessment zone for 1987 and 1988 are presented in the two tables that follow Table 2.2.

Table 2.2. Average scores and standard deviations on two variables for Red Sea Province, 1987 and 1988.

 

Drought

Impacts

Food

Insecurity

Total

 

1987

1988

1987

1988

1987

1988

Mean

3.25

5.10

6.10

6.89

9.35

12.00

SD

0.76

1.05

1.72

2.03

2.06

2.72

Table 2.3. Drought Impacts and food insecurity scores, Red Sea Province, 1987.

DROUGHT IMPACTS FOOD INSECURITY

Zone

Rain

Veg

Sub

Cash

Food

Stock

Econ

Sub

TOTAL

Deviation

     

Total

Crop

Crop

Cond

Acts

Total

 

from Mean

1a Port Sudan-Tokar Coast

2

1

3

2

2

2

2

8

11

1.65

1b S. Tokar Coast

1

2

3

1

3

2

2

8

11

1.65

2 S. Tokar Central

2

1

3

1

1

2

0

4

7

-2.35

3 S. Tokar Mountain

2

2

4

1

1

2

0

4

8

-1.35

4 Khor baraka-langeb

2

2

4

3

3

2

2

10

14

4.65

6 Derudeb Khor langeb

1

1

2

0

0

2

2

4

6

-3.35

7a RPS-Halaib Central Mountain

1

2

3

1

1

3

1

6

9

-0.35

7b Sinkat/Erkowit Mountain

1

1

2

1

1

2

2

6

8

-1.35

8a Tahamyam East

2

1

3

1

1

2

2

6

9

-0.35

8b Haya,Tahamyam

1

1

2

1

1

2

2

6

8

-1.35

8c Haya, Khor 'Arab Basin

2

2

4

1

2

2

1

6

10

0.65

12 Haya North

2

2

4

1

2

2

1

6

10

0.65

16 Halaib Central Mountain

2

2

4

1

2

3

1

7

11

1.65

17 Halaib Coast South

2

1

3

1

1

3

2

7

10

0.65

18 Halaib Mountain Central

2

2

4

1

2

3

1

7

11

1.65

19 Halaib Mountain North

1

1

2

1

2

2

1

6

8

-1.35

20 Halaib Coast North

2

2

4

1

2

3

2

8

12

2.65

24 RPS-Halaib Central Mountain

2

2

4

1

2

2

1

6

10

0.65

25a Derudeb Central

2

1

3

0

0

2

0

2

5

-4.35

25b Derudeb West

2

2

4

1

2

2

0

5

9

-0.35


Map 2.2. Drought impacts and food Insecurity, Red Sea Province, 1987.

Table 2.4. Drought Impacts and food insecurity scores, Red Sea Province, 1988.

 

DROUGHT IMPACTS

FOOD INSECURITY

Zone

Rain

Veg

Sub

Cash

Food

Stock

Econ

Sub

TOTAL

Deviation

     

Total

Crop

Crop

Cond

Acts

Total

 

from Mean

1 Sarara A

1

3

4

0

0

3

0

3

7

-5

2 Halaib west

no data

3 Khor 'alaagi

2

3

5

0

0

2

2

4

9

-3

4 Sarara B

3

2

5

0

0

2

2

4

9

-3

5 Halaib town

1

3

4

0

0

3

3

6

10

-2

6 Muhammed qul A

1

1

2

0

0

2

3

5

7

-5

7 Gebeit al-ma'adiin

1

3

4

0

0

3

3

6

10

-2

8 Khor oko

3

3

6

0

3

3

3

9

15

3

9 Muhammed qul B

2

3

5

0

0

3

3

6

11

-1

10 Khor arba'at A

2

3

5

0

0

2

3

5

10

-2

11 Khor tumaala/Oko

3

3

6

3

3

3

3

12

18

6

12 Khor 'amuur

3

3

6

0

3

3

2

8

14

2

13 North haya

3

2

5

1

1

2

1

5

10

-2

14 Khor agwampt

3

3

6

0

2

2

2

6

12

0

15 Khor 'udrus B

3

3

6

0

1

2

3

6

12

0

16 Khor 'udrus A

3

3

6

0

3

3

3

9

15

3

17 Khor arba'at B

2

1

3

0

0

2

3

5

8

-4

18 Port Sudan

2

2

4

1

1

3

3

8

12

0

19 Suakin

3

3

6

0

0

3

3

6

12

0

20 Khor akwaat/sallum

3

3

6

0

3

3

3

9

15

3

21 Gebeit/'agaba

3

3

6

0

2

3

3

8

14

2

22 Ayshaf A

3

3

6

0

2

2

2

6

12

0

23 Ayshaf B

3

1

4

0

1

3

3

7

11

-1

24 Erkowit/hadirbab B

3

1

4

0

1

2

1

4

8

-4

25 Hadirbab A

3

3

6

0

3

3

2

8

14

2

26 Khor asot

3

2

5

1

2

2

3

8

13

1

27 Wahribab

3

3

6

0

2

3

3

8

14

2

28 Khor osir

3

3

6

0

0

3

3

6

12

0

29 Suakin/Tokar road area

2

3

5

2

3

2

3

10

15

3

31 Coastal S. Tokar

1

2

3

1

1

2

2

6

9

-3

32 Central S. Tokar

2

2

4

0

2

2

3

7

11

-1

33 Mountain S. Tokar

2

3

5

0

0

2

3

5

10

-2

34 Khor baraka

3

3

6

3

3

2

3

11

17

5

35 Hamashkoreb

Grouped with zone 34

36 Khor langeb

3

3

6

2

2

3

3

10

16

4

37 Derudeb east

3

3

6

0

2

2

3

7

13

1

38 Khor langeb

3

2

5

0

2

2

2

6

11

-1

39 East haya

3

3

6

1

1

3

2

7

13

1

40 Derudeb west

3

3

6

2

3

2

2

9

15

3

 


Map 2.3. Drought impacts and food insecurity, Red Sea Province, 1988.

Two areas experienced low drought impacts and food insecurity in 1987 in Red Sea Province: the Khor Baraka watershed (Zone 4) and the coastal strip from Halaib Town to Egypt (Zone 20). The rest of the coastal strip (Zones 1A, 1B, and 17), the central highlands in Halaib District (Zones 16, 18), and the west central portions of Red Sea Province (Zones 12, 24, and 8C) experienced moderately low drought impacts and food insecurity in 1987. Those areas that experienced moderately high drought impacts and food insecurity in 1987 were west of Halaib (Zone 19), the central and southern Red Sea Hills Zones 7A, 7B, 8A, 8B, and 3), and the Braytek basin in the southwest (Zone 25B). Those areas with the worst scores were two: southcentral Red Sea Province (Zones 25A and 6) and the foothills of the South Tokar mountains (Zone 2) (see Map 2.2).

In 1988 there was a dramatic reversal of position; in general those zones that scored highest in 1987 scored lowest in 1988. Lowest drought impacts and food insecurity was found in the south of the province in Zones 29, 30, 34, 35, 36 and 40), in the centre in the 'Udrus and Akwaat valleys, and in the north centred on Khors Oko and Tumaala in Zones 8 and 11. Moderately low positive scores were registered along the Port Sudan to Suakin coast (Zones 18, 19), in the Khor 'Amour (Zone 12), Agwamt and western 'Udrus watersheds (Zones 15, 14), the Tahamyam-Haya area (Zones 22, 25, 26, 27, 39) into Khor Osir (Zone 28) and south into eastern Derudeb (Zone 37). Zones scoring moderately low below the mean (negative scores) were scattered around the province. This group is composed of Zones 5, 7, 9 and 10 along the north coast, Zones 13 and 28 in the western and southern interior, and Zones 32 and 33 in the South Tokar mountains. The Zones scoring highest in Drought Impacts and Food Insecurity were, for the most part, located in the north of the province. These Zones are 1, 2, 4 and 8. The three other areas scoring the lowest were scattered around the province with no apparent pattern. These zones are 17, 24, and 31.

The figure below presents a view of the differences between the two years. Variables measuring rainfall or a rainfall related product such as pasture, vegetation, agriculture, or agricultural employment all scored higher in 1988. The scores for 1988 were on average 1.85 points higher than 1987 for the Drought Impacts variable and 0.79 points higher for the Food Insecurity variable and 2.65 points higher on both variables. The difference in percent is 57, 13 and 28 percent respectively.


Figure 2.1. Drought Impacts and food Insecurity, Red Sea Province, 1987 and 1988 zone scores.

Map 2.4 below presents change from 1987 to 1988- in the Drought Impacts and Food Insecurity scores. The scores are not marked in standard deviations as in Maps 2.2 and 2.3 but in points change.


Map 2.4. Change in Drought Impacts and Food Insecurity, Red Sea Province, 1987 to 1988.

 

Conclusion

Considerable change in drought impacts and food insecurity has occurred from 1987 to 1988 in Red Sea Province as measured by the method described in the present paper. This change was due to the excellent rains of 1988 which fell generally over southern and central Red Sea Province. The rains were so good that pasture was abundantly available in and outside of khors and areas were cultivated that had never been cultivated before. There were areas where rainfall was good but vegetation and other variables scored low.

Our method appears to be a useful technique for the rapid assessment of large areas, however, there may have been some problem with measuring the influence of intervening variables, for example, we were not able to assess the economic significance of camel and sheep smuggling in the northern areas of the province. Had we been able to do so the scores for some of these areas might have been higher. Specific issues relating to the method and results will be addressed in the Discussion and Limitations of the Study sections below.

 

Discussion

Although the method for the rapid assessment of large areas used in the present study appears useful, there are some problems in the interpretation of Maps 2.2 and 2.3 that need to be addressed. The maps themselves are not directly comparable because each zone's value in the map is influenced by the scores of the other zones. While this is a useful method to understand the relationship between the zones in one year it is less useful when comparing zones between years. For example, a change from best to worst for a zone between the two time periods does not necessarily mean any great change in the drought impacts or food insecurity in that zone. The change may be related, instead, to change within other zones that alter the position of the mean value and the position of all other values to the mean. This is what happened between 1987 and 1988 and it reflects the extreme annual variability of the environment of the southern and central portions of Red Sea Province. From 1987 to 1988 the southern part of the province, with the exception of the perennially well-off Khor Baraka basin and the lagging South Tokar District, leapt from last place to first place, principally because of the unprecedented rainfall. This caused the position of the northern zones, ordinarily receiving an unpredictable scattering of from 25 to 50 mm of rainfall annually, to apparently decline. These northern areas are in fact relatively immune from drought because they exist is a state of perpetual aridity.

In order to address this problem (and also to standardise the units of comparison) Map 2.4 was made. Map 2.4 presents a direct comparison of the raw scores for each zone on the map that had observations for both years. Indeed, the greatest changes took place where there was the greatest potential for environmental variability - in the southern and central parts of the province. The relatively low change in one area that received much rainfall, Zone 13 (1988), in the southwest of the province, may reflect the infestation of locusts in that area and also to its east toward Suakin. The extreme difference from 1987 to 1988 at the northern tip of the province was exactly -5.

Poor rain in 1988 was the reason why area was classed so low in 1988 but as it is a borderline case perhaps it would best be classed with the next group up, the -2 to -4 class. Relative lack of change in the northern areas as mentioned above reflects the perennial state of affairs in this area. The northern exception is the Khor Oko area which scored above the mean in 1987 and well above the mean in 1988. The good rains of 1988 were responsible for this as well as the nationally and internationally connected social support network of Shariif Aderob of the Mosque at Tumaala. The same observation holds for the Mosque of Shaykh Sulaymaan at Hamashkoreb in the extreme south of the province. The two religious settlements provided assistance to destitute people during and after the drought. The population of children in the rural khalwas, religious training centres associated with the mosques, rose dramatically during the drought as did the founding of khalwas.

Zone 24, the Erkowit area, registered a 4 point decline from 1987 to 1988. Although rainfall was good, vegetation, cash crops, food crops and employment opportunities were not. There is evidence to indicate that there have been significant changes in vegetation in the Erkowit area (Vetaas 1989). These changes may have had impacts on livestock production and recovery. It is known from reports that planting in the Erkowit area had to be done several times because of excessive flooding and crop damage. This may have been responsible for the food crop problems.

The only area that had a relatively high decline in points from 1987 to 1988 in the south of the province was the coastal strip from 'Agig almost to Garora The poor rain along this portion of the coast plus the high numbers of refugees from Eritrea living in poor conditions resulted in a low score

Based on our study what can we say about the economic recovery from drought? Quite simply we may state that at present those areas that scored poorly in 1988 did so for reasons different from those relating simply to drought or the general economic climate. In South Tokar, for example, the principal reason for poor scores was war in Eritrea and the influx of refugees. It should be mentioned that the majority of these refugees are indistinguishable from the people living in South Tokar District. The only difference is that, unlike their Sudanese cousins, they have no land or cultivation rights in Red Sea Province. They used to seasonally migrate with the rains from Eritrea to Red Sea Province in search of grazing and employment. When the Sudanese-Eritrean border was closed and mined by the Ethiopian government many of these people were trapped on the Sudan side and lost their livestock in the dry season. When the border was reopened after the Eritreans took the border areas in the mid-1980s it was too late for these people; they were already destitute.

The environment of northern Red Sea Province is an example of low potential for change. The rainfall is scattered and low. The economy in northern Red Sea Province, however, is one of the strongest regional economies in the Sudan. This economy has two linked components: a pastoral economy centred on camel and sheep raising for sale to Saudia Arabia and Egypt and a settled economy which is involved in the smuggling of other goods. The variables used in the present study may not have measured the strength of the northern economy as well as expected.

Lack of recovery in certain areas of Red Sea Province today is less related to environmental or economic factors than to political instability and the specific social conditions of individuals and should be addressed in a more appropriate manner than that done presently by international donors. A specific programme to address the needs of people marginalised by the Eritrean conflict who live outside the camps in South Tokar should be undertaken. Efforts should be undertaken to target vulnerable groups: divorced or widowed women with dependent children and limited family support, pregnant and lactating women and children of weaning age.

 

Limitations of the study and comments on the research method

Problems we encountered during the course of the work are listed below.

1. The units of analysis used in the study in 1987 were too big and did not reflect human land use. Smaller units. perhaps clusters of villages, would have been more appropriate. The costs of data collection are a consideration, however. For 1988, several of the zones were still inordinately large. With more information (see below) they could be trimmed into coherent subunits.

2. The concept of the uniform spatial unit was difficult for some of the field workers to grasp. They invariably attempted to classify subareas of the subecozones rather than synthesise and generalise over the entire area. Perhaps this problem would be alleviated by the use of smaller, easier to handle, spatial units.

 

An alternative method

Although expanding the complexity of the work goes counter to our intention to explore alternative, low-technology methods of areal assessment, this type of research would benefit from the high technology approach. The use of the Normalised Difference Vegetation Index (NDVI) maps rather than subjective assessments of rainfall and vegetation quality would have gone far to reduce error in classification. The NDVI is prepared on a monthly basis for the governments of most drought-prone African countries by the United States Geological Survey, National Mapping Division at the EROS Data Center in the United States. It is funded by the Africa Bureau of the United States Agency for International Development (USAID). NDVI images are produced from the United States National Oceanographic and Atmospheric Administration's Advanced Very High Resolution Radiometer (AVHRR) satellite data. The scale of the imagery is 1:2500000 and the resolution is 1 km2. Reflectance values of vegetation are on a greenness scale from -1.0 to 1.0, the lower limit being equivalent to bare rock and the upper to green fields of wheat.

The study would have benefited from the use of more variables, for example, rainfall in millimetres, cropped and harvested areas, human and livestock populations, number of migrant workers, wage rates and destinations, security, number of refugees, malnutrition rates, and locust damage to crops. These types of data together would go well in a principal components or factor analysis. Principal components and factor analysis are used to bring together variables and different types of data and create new variables that express the relationships between the original variables. These new variables can be mapped in meaningful ways. There are two interrelated reasons to use principal components or factor analysis in a study such as the present one4:

1. To identify groups of intercorrelated variables.

2. To create new variables through combination of old variables.

Intercorrelated variables are independent variables that measure the same thing in different ways. In combining the variables we define the "thing" we are measuring. Sometimes this is called "fishing around in the data." One variable, for example, human population, may not explain the distribution of livestock in Red Sea Province at a given time during the year. The aggregation of more than one variable will do so. For example, what is the relationship between the variables, rainfall, tribal affiliation, human population, livestock populations and the Braytek basin? It is a good guess that these variables may explain it. The factor analysis combines such variables and creates factors instead. Out of 25 variables, for example, the factors produced by factor analysis would be about 4. Each factor expresses a characteristic or a concept. For example, a factor composed of the variables, human population, livestock population, rainfall, and location possesses the characteristics of rainfall, rural, areas of good pasture production, people, and location. It may be called "areas of good grazing and human and livestock concentration". In Red Sea Province, where this variable is found to be high one can expect all that the variable measures to exist there. Where it is low, the opposite is expected. Other groups of variables may be so grouped. This reduces many of the headaches of determining significant variables and also creates important variables from variable that alone would not be significant.

The use of a Geographic Information System would also be a great help for similar studies that use more variables. A Geographic Information System (GIS) is a computer programme that stores, analyzes and makes maps of data such as those collected for the present study. A GIS has the power to manipulate masses of data, do much of the statistical work done by expensive statistics programmes (which, these days, may include the creation of factors from groups of variable), and automate the process from data to maps (see Clarke (1986) and Lillesand and Kiefer (1987) for further information). The investment necessary for the high technology approach would be more appropriate for large and long term programmes with generous budgets and secure financing. A prograrnme such as this is more appropriately conducted on the national or international level rather than at the provincial level. A system such as or similar to that described in the present paper would go a long way in providing useful data for drought impacts and food insecurity assessments on the regional or national level. The most important consideration in setting up such a system is to keep the unit of analysis, the cell or zone, as small as possible. If the unit of analysis is too big it becomes insensitive or masks the differences within the unit. Ideally, differences within a unit should be minimised. Good criteria in constructing a unit would be uniform economic activities, land use, land cover, ethnic, cultural or familial uniformity, and urbanisation or linkage to urban areas. Although the District Councils in the Sudan may be of an appropriate size and homogeneity for zoning in a meaningful way, there may be traditional systems of areal zoning that are more useful, for example, lineage or ethnic areas. In the case of the Sudan, it may be more convenient to use the District Councils because they are a unit of data collection on a variety of topics. For example, data are collected at the District Council headquarters on cultivated and harvested areas within the District Councils, rainfall and market prices for cereals and livestock. It is here that data for the Islamic social security system (from the zakaat) are collected. It should be noted that the District Council can be broken down into any number of units because of the way the data are collected. For example, data on cultivated and harvested areas are collected by khor. If a particular khor fits better into some other spatial grouping than the District Council, then it can be regrouped. Also available are data on rainfall (Meterological Department in Khartoum) and wadi flooding (National Water Corporation in Khartoum). Rainfall data are available on a daily, monthly, or annual basis. Available flood data, collected from permanent gauging stations around the country, concern the number of floods, the duration of each flood, the maximum discharge in cubic metres and the total flow per flood in cubic metres. In Red Sea Province there are seven such gauging stations The agricultural schemes throughout the Sudan collect their own data on rainfall and flooding as well. NDVI maps of vegetation on a monthly basis are available, as mentioned above, but in deeply incised areas of the Red Sea Hills their usefulness is limited because the large unit of analysis (1 km2) mixes the reflectance values for the khors with the mountains. Landsat Thematic Mapper data would be more appropriate but are more expensive and take longer to process than the NDVI data.

 

References

Clarke, R. (1986) The handbook of ecological monitoring. Clarendon Press, Oxford

Environmental Research Group Oxford (1989) Personal communication.

Johnston, R.J. (1980) Multivariate statistical analysis in Geography. Longman, Essex.

Lillesand, T.M. and Kiefer, R.W. (1987) Remote sensing and image interpretation. Second edition. John Wiley and Sons, New York.

Rummel, R.J. (1967) Understanding factor analysis. Journal of Conflict Resolution, 11: 444-480.

Watson, R.M., Tippett, C.I. and Rizk, F. (1975) Sudan national livestock census and resource inventory. Volume 15, the results of an aerial census of resources in Red Sea Province in December 1975. Sudan Veterinary Research Administration, Ministry of Agriculture, Food and Natural Resources, Khartoum.

 

 

3. Drowght, food stress, and the flood and rainfall record for Red Sea Province. Roy Cole

 

Summary

In this paper the flood record for 9 watersheds in Red Sea Province, 1 watershed in Kassala Province, and the records of 19 rainfall gauging stations in and around Red Sea Province were examined. The purpose of the study was:

1. To obtain a more precise understanding of the extent and nature of the drought of the early 1980s and during other periods in Eastern Region.

2. To compare information obtained from the flood record with information obtained from rainfall gauging stations around Eastern Province to see what differences and commonalities exist between the two measures of precipitation. `

3. To compare qualitative estimations about drought and food stress in the past with the flood and rainfall record.

4. To make available to policymakers, government, and other researchers the historical record for the study area.

The findings of the study indicate that prior to the 1980s, severe drought was a local phenomenon in Red Sea Province but that in the early 1980s (generally from 1983 to 1984), severe drought became general. However, precipitation and flood data show no general downward trend over time for the area of study.

It was found that the well-known famine of 1948 was not related to severe drought; it was related to economic factors. Severe drought impacts of the early 1970s were felt along the coast and mountain areas that receive winter rainfall. It is notable that the interior watersheds of record had above average flooding during the same period The interior of the province and the central Red Sea coast experienced the greatest drought impacts in 1983 and 1984, when floods as well as rains failed.

 

Introduction

We do not have a clear understanding about the extent and the severity of the drought experienced in the Eastern Region of the Sudan during the early 1980s, nor do we have much information concerning previous drought in the area A drought is generally held to have occurred simultaneously over the Red Sea Province, Kassala Province (together the Eastern Region), Eritrea, and Ethiopia sometime in the early 1980s and a widespread famine is reported to have occurred in 1985. The Eritrean and Ethiopian drought, complicated by a long civil war, is well known. The present study was conducted to examine the distribution in time and space of the less well known drought in the Eastern Region of the Sudan that occurred in the early 1980s and other droughts that have occurred in the past.

The flood and rainfall record forms the basis for the present examination of the distribution of drought in the Eastern Region.

In this paper the flood record for 9 watersheds in Red Sea Province, 1 watershed in Kassala Province, and the records of 19 rainfall gauging stations in and around Red Sea Province will be examined. The study has four purposes:

1. To obtain a more precise understanding of the extent of the drought of the early 1980s in the Eastern Region as well as the droughts that preceded the 1980s.

2. To compare information obtained from the flood record with information obtained from rainfall gauging stations around Eastern

Province.

3. To compare qualitative estimations about drought and food stress in the past with the flood and rainfall record.

4. To make available to policymakers, government, and other researchers the historical record for the study area.

Although purposes one and two are important and form much of the discussion of the present paper, it is purpose four that is most important to the author. It is in the endeavour to contribute to the growing database on Red Sea Province that the present paper was written.

In the following discussion of the flood and rainfall records, first a general discussion of precipitation patterns in and around Red Sea Province will be presented. A definition of drought will then be formulated and discussed. After this discussion, a section on the flood record will be presented followed by a section on the rainfall record. A specific discussion of the measurement of drought impacts for each method of measurement will be found in a summary at the end of each section. A comparative discussion of the measurement of drought impacts by both methods will be reserved for the penultimate section on the measurement of drought impacts.

 

Precipitation In Red Sea Province

Precipitation in Red Sea Province occurs in two seasons, summer and winter. Summer rainfall (July to September) occurs as a result of the northward movement of the Inter-Tropical Convergence Zone (ITCZ). This 600 kilometre wide zone of humid air moves seasonally across the entire Sudano-Sahelian zone of Africa and is the source of the precipitation in that zone; the heaviest rainfall occurs in the southern parts of the Sudano-Sahel and the least in the southern Sahara Precipitation during this season falls throughout the interior of the province to approximately the central ridge of the Red Sea Hills from the southern districts of Red Sea Province to central Halaib District in the north.

Coastal Red Sea Province, generally dry throughout the summer season, receives rainfall in the winter months from November to February and heavy dew up until the end of April. This season of precipitation is caused by the northeast Trade Winds (called the harmattan in West and Central Africa). They are dry winds that transport water vapour from the Red Sea and deposit it in the form of rain and dew along the coast and mountain areas of Red Sea Province. These winds blow all year long but achieve their maximum during the winter months. Consequently, rain or dew may occur at any time of the year along the coast in Red Sea Province.

The effect of the Red Sea Hills on precipitation in both seasons is important. The Hills increase the precipitation during the summer season by forcing moist air into cooler, upper elevations where it condenses and falls as rainfall or is deposited on the ground as dew. Regarding the coastal zone, it is doubtful whether there would be any precipitation during the winter season without the lifting effect of the mountains. Areas located in a central position along the north-south axis of the Red Sea Hills as well as the khors flowing to the coast or interior fed by these hills benefit from two rainy seasons. In the summer season heating by the sun can cause local instabilities (thermal convection), uplift of air parcels, and rainfall (see ElTom 1989).

Mahdi Amin El-Tom (1975) distinguishes five precipitation zones in Red Sea Province. Two periods of rainfall can be distinguished: November to January and July to September.

Table 3.1. El-Tom's rainfall zones for Red Sea Province.

Area

Rainy Season

Coastal Eritrea to Khor Arba'at delta

November to January

Coastal Khor Arba'at delta to Halaib

October

Mountain and coastal northern Red Sea Hills

November

Mountain northwest

July to August

Interior southwest

July to September

 

Flood and rainfall records: problems and possibilities

The rainfall record in most third world countries is incomplete. Piecing together a complete picture of precipitation is further complicated by the uneven distribution of rainfall in arid and semi-arid areas and the thin distribution of rainfall gauging stations. Rainfall gauging stations are generally located where there a major concentrations of human population, not necessarily where the rain is. If the rain is not where the gauging station is located then it is not measured. Such measurement error could mask the difference on paper between a good rainfall year and a poor one. It is common in Red Sea Province to find no rainfall at a gauging station for a year or series of years but at the same time find floods in nearby khors because of unmeasured rain falling elsewhere.

The watershed gauging station, in contrast to the rainfall gauging station, is situated on a vast collecting basin. Because the unit of measurement encompasses a large contiguous spatial unit, the catchment basin, the chances of a "miss" of information are smaller than with the rainfall gauging station, which measures phenomena at a point. A drawback of flood data, however, is that where the river bed is permeable measurable amounts of runoff can leak out of the system and remain unmeasured. This problem is minimised to a great extent by the incidence of thick clay pans in the beds of the khors and along waterlines and by the rocky nature of the terrain. In general, the khors are sealed and runoff from the mountains is close to 100%.

In the end, however, the flood record suffers from the same problem as the rainfall record: it is incomplete. Flood records should be used in conjunction with rainfall records to provide a more complete picture of precipitation history than rainfall records alone.

A more perplexing problem, and one which is common to both types of data, is what does one make of the results? To interpret them in a meaningful way requires that they be linked to human experience. In many areas of the world rainfall data are used to predict crop yields. In Red Sea Province this is difficult to do because rainfall is extremely low, unevenly distributed, and agriculture is dependent on floods rather than rainfall. For reasons mentioned above, rainfall and floods may not covary well. Two uses to which the flood data may be put are the prediction of annually cultivated areas and the prediction of areas of pasture production. Flood data would be more useful than rainfall data in predicting agricultural activity or rainy season pasture production in Red Sea Province because of the reliance of both activities on the flood plains, grassy or wooded alluvial fans, and khor beds. Cultivated area can be predicted from the flood using the equation Y = mX + b, where Y equals the dependent variable, cultivated area, X equals the flood, m is the intercept, and b is the slope. Pasture production can be treated in the same way. Historical data on cultivated area and harvested area are kept by the District Councils (Majlis) throughout Red Sea Province. The author would have liked to include as a central point in the present paper a model of agricultural and pastoral production in Red Sea Province based on that presented above. Due to circumstances beyond his control he was unable to obtain the data on cultivated areas collected by the Sudanese government.

Recently, scientists and policymakers have turned to vegetation and crop greenness as an important variable to examine when assessing drought impacts. To do this they use data provided by satellites of the areas of interest. The sensors in the satellite measure the greenness or "vigour" of the vegetation on a month-by-month basis. These data are then indexed with rainfall data and mapped for publication and distribution, For a deeper discussion of NDVI see the paper, Measuring drought impacts and food insecurity in Red Sea Province" in this collection.

Map 3.1 below presents the location of flood and rainfall gauging stations throughout Red Sea Province. Khor Sallum, named after Sallum railroad station is called Khor Akwaat on the map. This is in conformance with local usage. The major drainage of the eastern Sudan is presented in Map 3.2 below.


Map 3.1. Flood and rainfall gauging stations, Red Sea Province.


Map 3.2. Drainage, Eastern Sudan.

 

A definition of drought

Understanding drought in Red Sea Province is dependent on understanding land use and its variability from year to year. In Red Sea Province, with the exception of favoured places such as the Tokar and Gash Deltas, strict dichotomies between activities such as the division between agricultural and pastoral have little meaning. Gradations in involvement are such that continuous is a more appropriate descriptor than dichotomous. This relationship is a result of the variable nature of the environment. This variability has implications for any definition of drought in human terms. To define drought in human terms both agriculture and pastoralism must be considered not as absolutes but as options that change from year to year.

The figures below present the long-term coefficients of variation for each of the khors and rainfall gauging stations and are presented to illustrate the variability of floods and rainfall in the study area.


.PNG Figure 3.1. C:oefficients of variation for nine khors.


Figure 3.2. Coefficients of variation for 18 rainfall gauging stations.

The interdependencies between agriculture and pastoralism in such a variable environment are so great that it would be more proper to speak of these interdependencies as complementarities. The figure below illustrates the variable relationship between floods and principal activity in the khors of Red Sea Province. A drought, as defined below, may be considered to fall somewhere between Pastoral and Pastoral and Agricultural. Severe drought, as is defined below, falls somewhere for two years running to the right of "little". "Little" means that few resources are available for any activity but those that are available are used by livestock: there has been little annual plant production and livestock subsist on Acacia tortillis and other browse.


Figure 3.3. Land use and flood size In Red Sea Province.

Years where the flood or rainfall varies between 1 standard deviation above and below the mean are notable for their frequency and should be considered as normal variation which people expect and for which, except for the most marginal of households, they are prepared. A year of flood or rainfall greater than 1 standard deviation below the mean is equivalent to little flood or rainfall. In human terms this means the failure of one annual crop and low production of annual grasses. However, crop residues will still be produced. On Figure 3.3 above pasture is the principal land use when the flood is over 1 standard deviation below the mean and a mix of pasture and moderate agricultural production when floods are around the mean. A good crop may be harvested despite the low rainfall the closer the flood or rain is to the mean (or above it) and if the rains or floods are well spaced. The more the flood is over the mean the more agriculture is practiced. It can, as it did in 1988, become the dominant activity of the khor.

One standard deviation accounts for over two thirds of the values on either side of the mean of any distribution. Beyond one and up to two standard deviations accounts for an additional third. Beyond two and up to three standard deviations accounts for the remaining fraction. 99.7 percent of all values will be within three standard deviations of the mean. Values greater than three standard deviations from the mean are generally considered outliers and are removed from calculations of central tendency. Data collected by different measures on different scales are often compared by transforming the raw data, in this case annual floods in millions of cubic metres and annual rainfall in millimetres, into standard scores called zscores. For example, a z-score expresses each annual observation of a flood series as a deviation from the average or mean value for the entire series of values. In this form the two types of measurement are directly comparable; that is to say, rainfall data and flood data, although they are measured in completely different units can be compared on the same scale. To calculate a z-score you must first calculate the mean and the standard deviation. The standard deviation is the square root of the deviation of each value in a data series from the mean. The formula for the standard deviation is


To obtain a z-score the mean is subtracted from each value in the data series and the resulting value is divided by the standard deviation.

Defining drought in terms of standard deviations below the mean seems significant in human terms because harvest surpluses are stored from year to year (up to 6 years see Cole 1989) and because pasture produced in one year can last for up to 3 to 5 years. In the western areas of Red Sea Province where interannual variation is the greatest ERGO (1989) found that pasture was usable for at least 3 years. Thesiger (1984) reported that pasture was usable 5 years after the last rain in the Empty Quarter of Saudia Arabia Further research is needed on this topic and in modelling agricultural and pastoral production in Red Sea Province. In any case, grain storage and the use of pasture for more than one year are mechanisms (among many others) that are used to smooth environmentally-induced interannual variation in livestock and human food supplies.

The cut-off of 1 standard deviation was used for 4 khors and 17 rainfall gauging stations. The khors are: Aiterba, 'Arab, Arba'at, Baraka, and Gash. The rainfall gauging stations are: 'Agig, 'Atbara, Derudeb, Erba, Gebeit, Gebeit Mine, Haya, Kassala, Muhammed Qul, Musmar, Port Sudan, Sinkat, Suakin, Tahamyam, and Tokar.

The 1 standard deviation criterion could not be used with khors or rainfall gauging stations where the coefficient of variation was more than 100% because the lower deviation was negative. Instead of the standard deviation, any annual flood or rainfall equal to or less than 20% of the mean was considered as a drought. This was done for 4 khors and 2 rainfall gauging station. The khors are: Gwob, Kass, Tahamyam, and 'Udrus. The rainfall gauging stations are: Arba'at and Halaib.

I would like to recapitulate the definition of drought above and to extend the definition to include severe drought where animal mortality and human impacts may be said to become important.

Drought is defined as one year in which the flood is equal to or greater than 1 standard deviation below the mean, or equal to or less than 20% of the mean Hood.

Severe drought is defined as two consecutive years where floods are equal to or more than 1 standard deviations below the mean, or equal to or less than 2096 of the mean flood.

 

The flood record

Prior to the 1950s, no flood records were collected in Red Sea Province except inundated area in feddans in the Tokar Delta. In the late 1950s and early 1960s, the Government of Sudan began collecting precise figures on flooding in five watersheds in Red Sea Province. In the mid-1970s, three additional stations were added The collection of data was relatively stable throughout the 1960s and 1970s. In 1988, the National Water Corporation had no budget for the monitoring of any of the watersheds except Khor Arba'at which is part of a permanent monitoring programme.

For each month in which flooding occurs, data is collected at the gauging stations on the following topics:

1. Date of each flood.

2. Duration of each flood in hours.

3. The maximum discharge of each flood in cubic meters per second.

4. The total volume of each flood in cubic meters.

Permanent flow, where it occurs, is treated separately on a month by month basis and added into the grand total for the station by month and year.

The following table lists the gauging stations, The date they began operating, the "e they terminated operating, and the authority responsible for maintaining the stations. By "present" it is meant that the station is still in use.

Table 3.2. Flood gauging stations of Eastern Region.

Station

Location

Start

End

 

Authority

 

Aiterba

Coast

1977

Present

National

Water

Corporation

'Arab

Interior

1960

Present

National

Water

Corporation

Arba'at

Coast

1957

Present

National

Water

Corporation

Baraka

Coast

1900

Present

Tokar

Delta

Board

Gash

Interior

1964

Present

Gash

Delta

Board

Gwob

Coast

1958

Present

National

Water

Corporation

Kass

Interior

1974

Present

National

Water

Corporation

Sallum

Coast

1958

1968

National

Water

Corporation

Tahamyam

Interior

1976

Present

National

Water

Corporation

'Udrus

Mountain

1960

Present

National

Water

Corporation

The table below presents the means, standard deviations and coefficients of variation for all watersheds of record.

Table 3.3. Means, standard deviations and coefficients of variation for ten watersheds In Eastern Region.

Station

Mean Annual

Standard

Coefficient

 

Flood (m3)

Deviation

of Variation

Aiterba

7174940

6721840

94%

'Arab

13586209

13219465

97%

Arba'at

25123895

22512259

90%

Baraka

76322*

44137

58%

Gash

67579*

25517

38%

Gwob

4185013

6630691

158%

Kass

8346966

8347522

100%

Sallum

4880734

4896680

100%

Tahamyam

1813798

2738385

151%

'Udrus

2583461

2847960

110%

* Data available only in feddans inundated. In the Sudan, 1 feddan is equivalent to 1 acre.

Both the standard deviation and coefficient of variation for the Khor Arba'at data are much lower if the outlier flood of 1987 (190 million m3 and 7 standard deviations above the mean) is removed from the calculation. The mean, standard deviation and coefficient of variation including the extreme value are 30630044, 37001635, and 121% respectively.

 

Drought and the flood record

One thing is immediately clear from the flood record, interannual variability of the flood is great: with the exception of Khors Baraka, and Gash interannual variability is near or over 100%; a very risky and marginal environment. The table below, taken from the data in Appendix 3.1, presents years of drought for each watershed.

Tab. 3.4. Drought and severe drought periods for tier" floodwater source areas in or near Red Se. Province.

Source Area

Drought

Severe Drought

Interior RSP

   

'Arab

1983-84

 

Kass

1983-84

 

Tahamyam

1974, 1987

1980-85

Mountain RSP

   

Aiterba

1985

 

Arba'at

1986

 

Gwob

1958, 1960, 1963,

1970-71, 1980-81

 

1969, 1977

1983-87

'Udrus

1961, 1965, 1970,

 
 

1983, 1985

 

Mountain Eritrea

   

Baraka

1936, 1955, 1957

1962-63

 

1960

 

Gash

1983

 

In the interior of the province and for Khors Baraka and Gash, which have their source in Eritrea, the 1970s were a decade of above average flooding. The major drought-affected area during the early 1980s was the interior of the province where Khor 'Arab, the agricultural and pastoral focus of many individuals for part of the year, failed to flood for two consecutive years. Khors Kass and Tahamyarn, tributaries of Khor 'Arab, present the same pattern.

Ike flood deficit in the Interior of Red Sea Province before and after the two years of complete drought created a calamity for which people were unprepared and informants in the area recalled no other similar period in their recent history except 1948, a year mentioned by many people as one of major famine and one for which we have no flood data. In addition, the Gash delta, a redoubt of pastoralism and one of the major agricultural areas for Red Sea Province, experienced a drought in 1983. Stern in

1985 estimated that there were 25000 people in camps in the Districts of Derudeb, Haya, and Sinkat. This figure represents between 6 and 9 percent of the rural population of Red Sea Province depending on which figures are used in estimating rural population in Red Sea Province (see Population and Human Geography in the Introduction). The Khor 'Arab basin drains much of two of the three districts mentioned in Stern's report.

 

The rainfall record

Data is available for 19 gauging stations around Red Sea Province: 17 within the boundaries of Red Sea Province itself and 2 near the province (Refer to the Map 3.1 of the flood and rainfall gauging stations). The record, as the table below indicates, is far from complete. Only nine of the 19 stations are still functioning today. The remainder stopped collecting data in the early 1980s, probably as a result of budgetary problems with the then Numeiry government.

Table 3.5. Location and years of record for 19 rainfall gauging stations in and around Red Sea Province.

Station

Lat.

Long.

Elev.

Location

Years of Record

'Agig

18 14

38 11

5

Coast

1921-38, 1944-88

Arba'at

19 49

37 20

120

Mountain

1943-62, 1964-68, 1973-87

'Atbara

17 39

33 58

348

Interior

1907-88

Delay

17 23

36 05

500

Interior

1975-84

Derudeb

17 35

36 06

510

Interior

1944-77

Erba

19 04

36 48

680

Mountain

1943-72, 1975-81

Erkowit

18 46

37 06

1095

Mountain

1943-52, 1965-72, 1977-78, 1981-1983

Gebeit

18 57

36 51

795

Mountain

1908-24, 1928-80

Gebeit Mine

21 03

36 20

640

Mountain

1944-78, 1980-81

Halaib

22 13

36 39

12

Coast

1953-88

Haya

18 20

36 22

640

Interior

1940-81

Kassala

15 28

36 25

NA

Interior

1901-39, 1942-88

Mohammed Qul

20 54

37 06

5

Coast

1953-75, 1978-80

Musmar

18 13

35 38

495

Interior

1948-76, 1980-82

Port Sudan

19 37

37 13

5

Coast

1941-88

Sinkat

18 50

36 50

870

Mountain

1920-82

Suakin

19 07

37 20

5

Coast

1890-1988

Tahamyam

18 20

36 32

690

Interior

1909-40, 1942-50, 1952, 1956-72, 1974-80

Tokar

18 26

37 44

20

Coast

1913-18, 1920-36, 1939-88

Table 3.6 below presents the mean annual rainfall coefficients of variation for the eight gauging stations with complete records. Only two stations have coefficients of variation that are greater than 100 percent. As a general rule for reasons mentioned above in the section concerning rainfall and the movement of the Inter-Tropical Convergence Zone, the more southerly the location of the gauging station, the lower the coefficient of variation.

Table 3.6. Years of record, mean annual rainfall, standard deviations, and co_ coefficients of variation for eight rainfall gauging stations In and near Eastern Region, Sudan.

Station

Years of

Mean Annual

Standard

Coefficient

 

Record

Rainfall

Deviation (mm)

of Variation

'Agig

63

136

85

63

Arba'at

40

39

51

105

'Atbara

82

68

50

74

Halaib

36

33

37

112

Kassala

86

307

84

27

Port Sudan

48

90

63

70

Suakin

99

157

127

81

Tokar

73

73

50

68

Table 3.7 below presents the decadal means for the eight gauging stations for which we have complete records. A general downward trend in the data is not clear. For three of the stations, Kassala, Port Sudan, and Suakin, a downward trend is evident. For the others the trend is upward or not clear.

Table 3.7. Decadal means from 1988 to the earliest complete decade for eight gauging stations In and around Red Sea Province.

Station

     

Decade

 

1988-79

78-69

68-59

58-49

48-39

38-29

28-19

18-09

08-99

'Agig

109

157

117

166

134

139

128

na

na

Arba'at

40

31

35

19

87

na

na

na

na

'Atbara

62

60

60

87

59

69

82

65

na

Halaib

28

6

57

48

na

na

na

na

na

Kassala

240

264

279

367

314

328

319

347

na

Port Sudan

53

66

115

103

116

na

na

na

na

Suakin

49

97

300

113

128

145

155

170

172

Tokar

64

55

98

77

83

45

70

91

na

These data are presented in the following figures to clarify trends. Figure 3.4 illustrates the downward trend of three stations while Figure 3.5 presents the upward or indeterminate trends of five stations.


Figure 3.4. Decadal rainfall means exhibiting a downward trend for three rainfall gauging stations In or near Red Sea Province.


Figure 3.5. Decadal rainfall means exhibiting an upward or indeterminate trend for five rainfall gauging stations in or near Red Sea Province.

 

Drought and the rainfall record

The same criteria used for defining drought for the khors is used in defining drought for rainfall. To reiterate, a drought is defined as one year in which the rainfall is equal to or greater than 1 standard deviation below the mean. or equal to or less than 20% of the mean rainfall. Severe drought, in contrast, is defined as two consecutive years where rainfall is equal to or more than 1 standard deviation below the mean, or equal to or less than 20% of the mean rainfall.

The rainfall record for all of the stations for which we have data in and around Red Sea Province are presented in Appendices 3 and 4, The table below presents drought and severe drought periods for the rainfall gauging stations for which we have data

Table 3.8. Drought and severe drought periods based on rainfall data for three geographic areas in Red Sea Province.

Area Coast

Drought

Severe Drought

'Agig

1945, 1960, 1964, 1986

 

Halaib

1958, 1969, 1982, 1984, 1988

 

Muhammed Qul*

1959

1971-73

Port Sudan

1949, 1973

1980-83, 1987-88

Suakin

1977, 1981, 1983, 1987

 

Tokar

1939, 1949, 1960, 1977, 1983

 

Interior

   

'Atbara

1914, 1918, 1926, 1935, 1941,

1912-13, 1982-84

 

1948, 1963, 1966, 1969, 1971,

 
 

1973

 

Derudeb*

1948, 1963, 1973

1983-84

Haya*

1941, 1970, 1973, 1975

1980-81

Musmar*

1948, 1960, 1973, 1980, 1982

 

Kassala

1902, 1926, 1930, 1958, 1963,

1943-44, 1984-85

 

1966, 1970, 1980, 1982

 

Tahamyam*

1919, 1948, 1971, 1980

 

Mountain

   

Arba'at

1948, 1951, 1969, 1974, 1977,

1953-57, 1980-81,

 

1987

1983-84

Erba*

1951, 1958, 1969, 1980

 

Gebeit*

1944, 1948, 1980

1971-74

Gebeit Mine*

1949, 1980

 

Sinkat*

1941, 1943, 1947, 1970, 1980

1977-78

* Incomplete record

Although the early 1970s were a period of deficit rainfall throughout sub-Saharan Africa, it is interesting that it was not registered as severe drought at the gauging stations in the Interior of Red Sea Province. There was, however, serious drought in the Mountain and Coastal zones during that time. Another interesting fact derived from the table is that there was no severe drought in the late 1940s, a recognised period of famine. This famine had little to do with drought. It was, rather, the result of war taxation of the colonies from 1939 to 1945, cereal price inflation associated with the war, and decline in the terms of trade of livestock to cereals which weakened the people of the province such that they were not able to cope with the normal variation of their environment. The same phenomenon happened in Mali in West Africa where the author did research on drought in the mid-1980s. In the Sudan, the Second World War was a boom period and a period of high commodity price inflation. Imports rose from 8,060,849 Egyptian Pounds (£E) to £E 41,966,091 from 1941 to 1451. Exports rose £E 8,895157 to £E 62,177,529 over the same period (Holt and Daly 1979). Serious problems accompanied these increases. Durra prices doubled from 1939 to 1945 and tripled from 1946 to 1948. Most northern (Nile valley) farmers benefited from the increase in farmgate prices, however, nonfarmers or those only peripherally involved in farming may have experienced a situation not unlike that experienced by many in Red Sea Province in the early 1980s.

 

Conclusion

In areas like Red Sea Province where almost all economic activity is confined to watercourses, it is good practice to use rainfall data in conjunction with the flood record to obtain a better picture of the extent and severity of drought. In addition to this obvious statement, there are five statements we can make about drought in and around Red Sea Province according to the available flood and rainfall records.

1. Floods and rainfall in and around Red Sea Province are highly variable: floods being more variable than rainfall.

2. There is no general downward trend in the rainfall or flood data, however, there are local downward trends.

3. Up to the early 1980s drought was a localised phenomenon in Red Sea Province.

4. There was no severe drought in the interior areas of the province in the early 1970s according to the flood record. There was, instead, above average flooding.

5. Severe drought was felt during the early 1970s in the Red Sea Hills, an area of predominantly winter rainfall.

6. The famine of 1948 was related to war taxation, cereals price inflation, and change in the terms of trade of livestock and only peripherally related to drought.

7. The area that has experienced the greatest drought impacts in the recent past in the area of study has been the Khor 'Arab basin and its immediate neighbours in 1983 and 1984 and the coastal around Port Sudan since the early 1980s.

 

Discussion

Despite the variability of precipitation in Red Sea Province, pastoralists and agropastoralists have relied on certain characteristics of the terrain in the province as insurance mechanisms. The principal insurance mechanism are the khors themselves, the focus of almost all rural economic activity. Just as it was said above that without the influence of the Red Sea Hills there would be no winter rainfall, it can be said that without the khors there would be no life in Red Sea Province.

Agriculture is not found outside the stream beds or alluvial fans and pastoralism is reliant on perennial and annual vegetation produced and maintained by annual inundations of the khors. The watershed acts as an enormous catchment that makes the most of spatially dispersed rainfall by channelling it to human users near the central course of the khors. As Evanari (1979) found in his study of ancient and modern water harvesting in the Negev, 10 mm of annual rainfall is enough to grow tropical fruit trees if the catchment area is 30 times greater than the area of cultivation. This is the principal behind land use in Red Sea Province. Furthermore, the vegetation in some large khors (and some small khors, particularly in the mountains) in Red Sea Province does not experience annual drought; the trees (and sometimes the grass) are always green because of subsurface water supplies.

Only in years of extreme and persistent drought or where there are other intervening variables does the insurance system break down, as it did in the Khor 'Arab basin in 1983-84, the place where destitute people were found crowding along the Port-Sudan Khartoum road begging for food in 1985, or in the coastal (and presumably, mountain) areas around Suakin and Port Sudan. Destitute people from these areas settled in Suakin, Port Sudan, and around Tokar town.

Although drought cannot be held responsible for the entire burden of misery shouldered by many people in Red Sea Province during the middle 1980s, it is a causal factor. Other factors which played a significant role in extending the misery during the early 1980s were principally economic inflation and, to a lesser extent, lack of economic diversification, and isolation. Of primary importance during the famine of 1984-85 was inflation of cereal prices and the turning of the terms of trade of livestock to cereals against livestock This inflation might have been meaningless if, with the exception of the Tokar Delta, local production in interior and coastal Red Sea Province had not collapsed for two years running. This was exacerbated by low production elsewhere in the Sudan. The economic impact of these factors in conjunction with drought are first felt by people who have a reason for being poor: single parent households (divorced or widowed women), families with unemployed or aged heads of household, refugees, and the incompetent.

The late mid to late 1980s brought a more promising outlook to Red Sea Province. It is unfortunate that no data are available from the National Water Corporation for 1988, a year of unprecedented rainfall and flooding. The National Water Corporation was not able to field their watershed monitoring teams because of the financial crisis in the Sudan. It is clear that flooding was probably two or three standard deviations above the mean throughout the province in 1988. The rainfall for the 'Atbara station. located at the confluence of the Nile and 'Atbara rivers, was almost 3 standard deviations above the mean and Kassala's was one standard deviation above the mean.

 

Limitations of the study

A major limitation to what we can say about drought in Red Sea Province is presented by the use of annual averages in the present study rather than monthly averages. The method used in the present study was insensitive to years in which floods were few but high in volume. This could have masked what technically should have been classed as drought. Caution needs to be exercised with the flood data obtained from the Tokar and Gash Deltas. Change in the number of feddans inundated over time may have been due to deteriorating infrastructure rather than drought. This is probably more of a problem in the Gash than in Tokar because of the canal system employed in the Gash

 

References

Cole, R. (1989) Land tenure, agricultural labour, drought and food stress in the Gash, Gash Dai, and Tokar agricultural areas. Oxfam Port Sudan.

Evanari, M. (1978) Ancient water management practices in the Negev. Land Reform,

Cooperatives and Development. Food and Agriculture Organisation. Rome.

Holt, P.W. and Daly, M.W. (1979) History of the Sudan: from the coming of Islam to the present day. Weidenfeld and Nicolson, London.

Mahdi Amin El-Tom. (1989) An outline of the climate of the Red Sea Region of the Sudan. Proceedings from a workshop on the Red Sea Area Programme, Khartoum, January 1989.

Mahdi Amin El-Tom. (1975) The rains of the Sudan. Khartoum University Press, Khartoum.

Stern, P.H. (1985) Proposals for developing low-cost small-scale irrigation in the Red Sea Province, Sudan. UNICEF Report GP 3378.01.

Thesiger, W. (1984) Arabian sands. Penguin Books, London.

 

Appendix 3.1. Annual floods for nine khors In Red Sea Province and Khor Gash in Kassala Province.

Table 3.9. Annual floods in cubic metres, Khors Aiterba, 'Arab and Arba'at.

Khor Aiterba

Khor 'Arab

 

Khor Arba'at

       

Year

Volume*

Year

Volume

Year

Flood

Flow**

Floods

       

Volume

Volume

and Flow

 

1977

6679425

1960

3883203

1957

14701480

2811170

17512650

1978

6266306

1961

14377191

1958

9846225

1347844

11194069

1979

5181696

1962

4640592

1959

47125198

999570

48124768

1980

6668739

1963

3647072

1960

10164516

0

10164516

1981

22745285

1964

33397056

1961

10835120

6410958

17246078

1982

7132806

1965

 

1962

10016618

5146416

15163034

1983

1585458

1966

6216335

1963

7264706

7264706

 

1984

948006

1967

40502232

1964

5216727

5216727

 

1985

0

1968

7397496

1965

     

1986

17952165

1969

13633582

1966

9146808

9146808

 

1987

3764457

1970

0

1967

13527184

13527184

 
   

1971

3194103

1968

     
   

1972

3453205

1969

521370

5907946

6429316

   

1973

16706136

1970

9309064

4398372

13707436

   

1974

17018364

1971

3778713

4229998

8008711

   

1975

21010873

1972

20019218

3825381

23844599

   

1976

31580204

1973

67608120

5154562

72762682

   

1977

8788883

1974

0

3867995

3867995

   

1978

51993344

1975

7158744

3561140

10719884

   

1979

25212744

1976

18105828

3998287

22104115

   

1980

2230092

1977

3918489

4281730

8200219

   

1981

7186457

1978

72601850

3847592

76449442

   

1982

5415246

1979

72317441

8300635

80618076

   

1983

0

1980

20496884

10109752

30606636

   

1984

0

1981

23504123

8536980

32041103

   

1985

4161672

1982

25856239

5596138

31452377

   

1986

23182884

1983

18060302

4339600

31452377

   

1987

17998695

1984

15493752

4520110

20013862

       

1985

26862210

2863584

29725794

       

1986

0

2315799

2315799

       

1987

1.88E+08

1992834

1.9E+08

       

1988

66974256

2737736

69711992

* All records are in cubic meters except Khors Baraka and Gash which are in feddans inundated.

** Permanent flow.

Tabel 3.10. Annual floods, Khors Baraka, Gash, and Gwob.

Khor Baraka

Year

Flooded Area

Year

Flooded Area

Year

Flooded Area

Year

Flooded Area

1900

19068

1922

42000

1944

86000

1966

27000

1901

13369

1923

49863

1945

114000

1967

112000

1902

14611

1924

35000

1946

96000

1968

111000

1903

18465

1925

31000

1947

65210

1969

28000

1904

39671

1926

33900

1948

26000

1970

110000

1905

33492

1927

60000

1949

56250

1971

40000

1906

36332

1928

75000

1950

168000

1972

82525

1907

50647

1929

125000

1951

38167

1973

88546

1908

27658

1930

100000

1952

50000

1974

124641

1909

45324

1931

85000

1953

134949

1975

167000

1910

51287

1932

99000

1954

27455

1976

56000

1911

43923

1933

70000

1955

2602

1977

118000

1912

53495

1934

66000

1956

177873

1978

128000

1913

30061

1935

25000

1957

22165

1979

35953

1914

76598

1936

82000

1958

71787

1980

61213

1915

38159

1937

43000

1959

117721

1981

55680

1916

122661

1938

85000

1960

23485

1982

63535

1917

93190

1939

54000

1961

214838

1983

78315

1918

42670

1940

50000

1962

12491

1984

35000

1919

47797

1941

64000

1963

22685

1985

95000

1920

135977

1942

76000

1964

117435

1986

88358

1921

54914

1943

71480

1965

29000

   
 

Khor Gash

Khor Gwob

Year

Flooded Area

Year

Flooded Area

Year

Volume

Year

Volume

1963

37802

1976

61892

1958

530855

1973

2756056

1964

70852

1977

64593

1959

27916104

1974

5499146

1965

49185

1978

65278

1960

0

1975

5503613

1966

60593

1979

54446

1961

18829481

1976

14543618

1967

103948

1980

54951

1962

16609946

1977

0

1968

45333

1981

 

1963

835452

1978

5760882

1969

80353

1982

50184

1964

610101

1979

4083526

1970

80557

1983

38358

1965

4877111

1980

0

1971

86970

1984

51531

1966

7861405

1981

821619

1972

74101

1985

55371

1967

1319211

1982

2773504

1973

72174

1986

46579

1968

441017

1983

0

1974

100007

1987

47000

1969

1930961

1984

0

1975

159441

1988

78000

1970

0

1985

0

       

1971

0

1986

0

       

1972

2047338

1987

0

Table 3.11. Annual floods, Khors Kass, Sallum, Tahamyam, and 'Udrus.

Khor Kass

Khor Sallum

Khor 'Udrus

     

YearVolume Year Volume

 

YearVolume

     

1974

24939468

1958

1382260

1960

842657

1975

3264158

1959

3920478

1961

9005

1976

7560343

1960

346285

1962

1792596

1977

4122927

1961

1196811

1963

4000417

1978

13073481

1962

1433899

1964

3579394

1979

27907570

1963

17542606

1965

447556

1980

3136285

1964

8411399

1966

12732343

1981

4607328

1965

9647082

1967

2449567

1982

3755871

1966

3754362

1968

1747935

1983

0

1967

3706716

1969

 

1984

0

1968

2346186

1970

0

1985

2432349

   

1971

3055169

1986

10878012

   

1972

983214

1987

11179737

   

1973

7973056

       

1974

1049670

       

1975

1071787

Khor Tahamyam

     

1976

1260379

       

1977

1080071

Year

Volume

   

1978

1356198

       

1979

 

1974

182719

   

1980

 

1975

4076658

   

1981

2996280

1976

9472397

   

1982

3457701

1977

769429

   

1983

0

1978

5158257

   

1984

6480234

1979

2151159

   

1985

0

1980

0

   

1986

1986624

1981

0

   

1987

4234689

1982

0

       

1983

0

       

1984

0

       

1985

0

       

1986

3582558

       

1987

0

       

 

Appendix 3.2. Annual flood 2 scores for nine khors in Red Sea Province and Khor Gash in Kassala Province.


Figure 3.6. Annual flood z scores, Khor Aiterba, 1977 to 1987.


Figure 3.7. Annual flood z scores, Khor 'Arab, 1960 to 1887.


Figure 3.8. Annual flood z scores, Khor Arba'at, 1957 to 1987.


Figure 3.9. Annual flood z scores, Khor Baraka, 1900 to 1986.


Figure 3.10. Annual flood z scores, Khor Gash, 1964 to 1988.


Figure 3.11. Annual flood z scores, Khor Gwob, 1958 to 1987.


Figure 3.12. Annual flood z scores, Khor Kass, 1979 to 1987.


Figure 3.13. Annual flood z score*, Khor Sallum, 1958 to 1968.


Figure 3.14. Annual flood z scores, Khor Tahamyam, 1974 to 1987.


Figure 3.15. Annual flood z scores, Khor 'Udrus, 1960 to 1987.

 

Appendix 3.3. Annual rainfall in mililmetres for 19 gauging stations in eastern region, Sudan.

Table 3.12 Annual rainfall in millimetres, 'Agig and Arba'at stations.

'Agig

     

Arba'at

 

1943

112.4

1960

35

1944

82.6

1921

125

1961

340

1945

103

1922

170

1962

80

1946

119

1923

70

1963

78

1947

99

1924

320

1964

25

1948

4

1925

125

1965

110

1949

74

1926

85

1966

60

1950

33

1927

60

1967

225

1951

4

1928

65

1968

80

1952

54

1929

27

1969

145

1953

0

1930

101

1970

100

1954

0

1931

248

1971

143

1955

0

1932

65

1972

180

1956

0

1933

68

1973

170

1957

4

1934

135

1974

100

1958

20

1935

320

1975

306

1959

21

1936

200

1976

142

1960

32.6

1937

120

1977

115.4

1961

40

1938

110

1978

168

1962

88

1939

 

1979

135.7

1963

 

1940

 

1980

84

1964

26

1941

 

1981

68.2

1965

24

1942

 

1982

108.7

1966

61

1943

 

1983

67.1

1967

14

1944

170

1984

326.8

1968

7

1945

40

1985

71.8

1969

 

1946

195

1986

41.9

1970

 

1947

105

1987

125

1971

 

1948

160

1988

62.8

1972

 

1949

320

 

1973

16.9

 

1950

65

 

1974

2.3

 

1951

390

 

1975

11.5

 

1952

60

 

1976

89.4

 

1953

120

 

1977

6.6

 

1954

190

 

1978

60.7

 

1955

70

 

1979

65.5

 

1956

125

 

1980

2.7

 

1957

175

 

1981

7.4

 

1958

145

 

1982

152.2

 

1959

140

 

1983

0.2

 
     

1984

0.1

 
     

1985

42.6

 
     

1986

84.3

 
     

1987

1.5

 

Table 3.13. Annual rainfall in millimeters, 'Atbara and Delai stations.

'Atbara

     

Delai

 

1907

100.1

1950

166.1

1944

110

1908

63.9

1951

67.3

1975

114.5

1909

79.8

1952

115.3

1976

42

1910

241.6

1953

106.6

1977

47

1911

141.3

1954

57.3

1978

63

1912

17.3

1955

25.9

1979

93

1913

0

1956

104

1980

38

1914

80.3

1957

41.6

1981

241

1915

1.8

1958

149.3

1982

148

1916

52

1959

85.3

1983

12

1917

28.7

1960

8.4

1984

5

1918

5.2

1961

134.4

   

1919

73.8

1962

53.2

   

1920

67.5

1963

16.4

   

1921

140.8

1964

51.1

   

1922

127.2

1965

86.9

   

1923

195.4

1966

16.2

   

1924

77.1

1967

55.6

   

1925

33

1968

96.2

   

1926

12

1969

14.7

   

1927

72.5

1970

93.8

   

1928

21.5

1971

11.4

   

1929

92.2

1972

55.2

   

1930

42.5

1973

11.9

   

1931

108.3

1974

51

   

1932

98

1975

92.2

   

1933

53.3

1976

68.8

   

1934

37.8

1977

111.7

   

1935

16

1978

91.9

   

1936

88.7

1979

105.9

   

1937

108.2

1980

63.3

   

1938

48.7

1981

27

   

1939

50

1982

18

   

1940

69.5

1983

15.5

   

1941

17.7

1984

1.1

   

1942

130.6

1985

33.3

   

1943

31.7

1986

41.3

   

1944

64.4

1987

71

   

1945

68.8

1988

238.9

   

1946

93.9

       

1947

55.7

       

1948

10.6

       

1949

39.4

       

Table 3.14. Annual rainfall In millimetres, Derudeb, Erba, and Erkowit stations.

Derudeb

 

Erba

 

Erkowit

 

1945

180

1942

264

1944

466.3

1946

110

1943

38.6

1945

250.2

1947

90

1944

91

1946

153.7

1948

17

1945

36

1947

87.8

1949

125

1946

115

1948

51.5

1950

440.2

1947

71

1949

134.6

1951

49

1948

64

1950

234.8

1952

178

1949

96

1951

40

1953

220.5

1950

257.5

1952

90

1954

88.6

1951

14

1953

 

1955

45.7

1952

53

1954

 

1956

117.3

1953

146.9

1955

 

1957

84.6

1954

59

1956

 

1958

147

1955

39

1957

 

1959

167

1956

125

1958

 

1960

31

1957

100

1959

 

1961

237.7

1958

29.9

1960

 

1962

82.3

1959

129

1961

 

1963

9

1960

61

1962

 

1964

97

1961

124

1963

 

1965

81

1962

70

1964

 

1966

84

1963

40

1965

156.2

1967

122

1964

147

1966

145.1

1968

153

1965

54

1967

254.4

1969

52

1966

105

1968

161.5

1970

106

1967

47

1969

43.5

1971

127

1968

112

1970

184.5

1972

33

1969

15

1971

136.6

1973

26

1970

60

1972

72.6

1974

37

1971

60

1973

 

1975

67

1972

65

1974

 

1976

176

1973

1975

   

1977

58

1974

1976

   
   

1975

74

1977

50

   

1976

58

1978

39.5

   

1977

59

1979

 
   

1978

134

1980

 
   

1979

138

1981

221.2

   

1980

32

1982

88.7

   

1981

46

1983

140.1

Table 3.15. Annual rainfall in millimetres, Gebeit and Gebeit Mine stations.

Gebeit

 

Gebeit

 

Mine

 

1908

71.4

1950

231.1

1944

119

1909

124.1

1951

65.2

1945

28

1910

88.5

1952

189

1946

63

1911

157.3

1953

105.3

1947

28

1912

99.2

1954

103.1

1948

30

1913

128.8

1955

85

1949

5

1914

119.8

1956

168

1950

93

1915

77

1957

52.2

1951

54

1916

158.1

1958

88

1952

68

1917

153.4

1959

326

1953

88

1918

97.5

1960

66

1954

38

1919

62.4

1961

171

1955

38

1920

108.8

1962

113

1956

0

1921

301.3

1963

76.5

1957

45

1922

96.6

1964

99

1958

39

1923

176.7

1965

69

1959

98

1924

21.4

1966

107.1

1960

242

1925

 

1967

142

1961

41

1926

 

1968

229

1962

12

1927

 

1969

58

1963

113

1928

64.2

1970

87.7

1964

44

1929

116.5

1971

17.9

1965

41

1930

77

1972

32.6

1966

72.5

1931

206

1973

3.3

1967

37.5

1932

173

1974

44.5

1968

69

1933

106.5

1975

122

1969

56

1934

144.7

1976

86

1970

59

1935

109.5

1977

83.5

1971

15

1936

159.2

1978

165

1972

12.5

1937

101.1

1979

286

1973

22.5

1938

66.3

1980

0

1974

50

1939

232.4

   

1975

19

1940

82

   

1976

60.5

1941

92.8

   

1977

99.5

1942

213.6

   

1978

15

1943

36.5

   

1979

 

1944

201.8

   

1980

0

1945

151.9

   

1981

33

1946

121.2

       

1947

92.2

       

1948

42

       

1949

77.1

       

Tab. 3.16. Annual rainfall in millimetres, Halaib and Haya stations.

Halaib

 

Haya

 

1953

57

1940

55

1954

17

1941

10

1955

124

1942

105

1956

38

1943

52

1957

48

1944

130

1958

5

1945

91

1959

18

1946

82

1960

53

1947

21

1961

60

1948

30

1962

83

1949

58

1963

36

1950

166

1964

12

1951

52.8

1965

26

1952

175

1966

168

1953

89.7

1967

32

1954

235

1968

77

1955

47

1969

4

1956

127.1

1970

15

1957

42.4

1971

0

1958

118

1972

0

1959

139.7

1973

7

1960

33.1

1974

5

1961

160.8

1975

3.8

1962

63.2

1976

20.7

1963

37.6

1977

1.7

1964

75.3

1978

4

1965

60.9

1979

59.5

1966

97.6

1980

10.4

1967

150.7

1981

31.1

1968

25

1982

0

1969

54.5

1983

52

1970

6

1984

1

1971

31

1985

69.2

1972

73

1986

10

1973

12

1987

49.2

1974

29

1988

1

1975

10

   

1976

70

   

1977

24

   

1978

42

   

1979

53

   

1980

0

   

1981

0

Table 3.17. Annual rainfall in millimetres, Kassala and Muhammed Qul stations.

Kassala

     

Muhammed Qul

 

1901

249

1948

205.6

1953

4

1902

199

1949

387.2

1954

41

1903

266

1950

440.7

1955

35

1904

320

1951

337.6

1956

5

1905

378

1952

284.7

1957

51

1906

280

1953

400.7

1958

31

1907

405.2

1954

359.3

1959

0

1908

343

1955

266.3

1960

78

1909

328.2

1956

429.4

1961

24

1910

329.8

1957

317.2

1962

101

1911

291.4

1958

451

1963

38

1912

302

1959

335.4

1964

23

1913

406.4

1960

293.3

1965

40

1914

333.8

1961

266.5

1966

171

1915

438.1

1962

285.3

1967

49

1916

487.9

1963

207.1

1968

90

1917

313.9

1964

464

1969

23

1918

236.1

1965

235.3

1970

52

1919

273.9

1966

131.1

1971

0

1920

387.7

1967

266

1972

0

1921

254.9

1968

305.5

1973

0

1922

314.6

1969

228.2

1974

45

1923

461.5

1970

220.2

1975

29

1924

330.5

1971

354.5

1976

 

1925

324

1972

222.7

1977

 

1926

135.3

1973

258.8

1978

50

1927

452.7

1974

334

1979

65

1928

253.4

1975

296.2

1980

7

1929

349.2

1976

243.7

   

1930

219.8

1977

212.3

   

1931

239.9

1978

270.1

   

1932

333.2

1979

280.1

   

1933

459.8

1980

194.7

   

1934

454.4

1981

239.8

   

1935

353.6

1982

217.2

   

1936

278.6

1983

249.4

   

1937

279.5

1984

98.8

   

1938

310.5

1985

145.9

   

1939

358.7

1986

306.9

   

1940

 

1987

271.3

   

1941

 

1988

393.8

   

1942

452.2

       

1943

214.2

       

1944

212.3

       

1945

350

       

1946

386.6

       

1947

333.9

       

Table 3.18. Annual rainfall In millimetres, Musmar and Port Sudan stations.

Musmar

 

Port Sudan

     

1948

5

1941

72.7

1980

10.9

1949

55

1942

58.3

1981

9.2

1950

161

1943

95.4

1982

80.4

1951

73

1944

149.9

1983

0.1

1952

153

1945

49.2

1984

83

1953

90

1946

164.6

1985

158.4

1954

89

1947

266.1

1986

66.6

1955

35

1948

75.6

1987

10.5

1956

82

1949

180.4

1988

13.9

1957

70

1950

212.9

   

1958

118

1951

209.6

   

1959

173

1952

67.1

   

1960

11

1953

28.1

   

1961

300

1954

14.8

   

1962

113

1955

45.2

   

1963

25

1956

44.6

   

1964

87

1957

144.7

   

1965

35

1958

84.8

   

1966

18

1959

68.9

   

1967

69

1960

132.7

   

1968

25

1961

121.6

   

1969

13

1962

196.8

   

1970

26

1963

164.4

   

1971

23

1964

47.4

   

1972

34

1965

144.6

   

1973

10

1966

76.3

   

1974

15

1967

30.9

   

1975

53

1968

165.2

   

1976

27

1969

38.6

   

1977

 

1970

47.4

   

1978

 

1971

108.6

   

1979

 

1972

59.9

   

1980

0

1973

8.7

   

1981

30

1974

32.7

   

1982

3

1975

63.8

   
   

1976

122.9

   
   

1977

72.4

   
   

1978

104

   
   

1979

94.6

   

Table 3.19. Annual rainfall In millimetres, Sinkat station.

1920

73

1965

54

1921

243

1966

88

1922

49.2

1967

146

1923

141

1968

109

1924

157

1969

71

1925

36.1

1970

7

1926

62.3

1971

45

1927

91

1972

75

1928

77.6

1973

86

1929

163.7

1974

95

1930

150.8

1975

64

1931

257.7

1976

102

1932

218.6

1977

31

1933

128.5

1978

20

1934

41.5

1979

94

1935

130.6

1980

12

1936

179.5

1981

68

1937

88.8

1982

50.1

1938

77.5

   

1939

168.4

   

1940

117

   

1941

11

   

1942

167.5

   

1943

25

   

1944

277

   

1945

117

   

1946

133

   

1947

20

   

1948

89.7

   

1949

114

   

1950

215.5

   

1951

80

   

1952

358

   

1953

213

   

1954

80

   

1955

43

   

1956

150

   

1957

51

   

1958

146

   

1959

404.5

   

1960

44

   

1961

82

   

1962

138

   

1963

58

   

1964

195

   

Table 3.20. Annual rainfall in millimetres, Suakin station.

1890

139

1930

43.4

1970

35.2

1891

166

1931

191.4

1971

149.3

1892

152

1932

176.9

1972

212.1

1893

198

1933

258.9

1973

51.7

1894

106

1934

80.5

1974

35.2

1895

401

1935

170.1

1975

49. 8

1896

617

1936

63.5

1976

281.1

1897

58

1937

185.1

1977

29.7

1898

443

1938

180

1973

73,6

1899

164

1939

104

1979

64,7

1900

151

1940

152

1980

36

1901

271

1941

138

1981

2.7

1902

452

1942

140

1982

80

1903

166

1943

100

1983

9.7

1904

178

1944

90

1984

35.8

1905

63.5

1945

118.8

1985

136.8

1906

155.3

1946

87.5

1986

37.9

1907

57

1947

273.5

1987

9.1

1908

64.9

1948

80

1988

72.9

1909

54.8

1949

131.6

   

1910

65.5

1950

159.2

   

1911

367.1

1951

95.6

   

1912

325.4

1952

48.6

   

1913

125.2

1953

33.5

   

1914

78.2

1954

35.5

   

1915

137.3

1955

67.5

   

1916

294.3

1956

121

   

1917

116.3

1957

116

   

1918

135.2

1958

323

   

1919

129.7

1959

159,5

   

1924

106.3

1960

157

   

1921

245.7

1961

334

   

1922

74.1

1962

515

   

1923

205.9

1963

626.3

   

1924

148.3

1964

99.5

   

1925

327.4

1965

450

   

1926

85.7

1966

. 242.6

   

1927

131.7

1967

98.9

   

1928

97.1

1968

321.9

   

1929

98

1969

52.1

   

Table 3.21. Annual rainfall In millimetres, Tahamyam station.

1909

147.1

1955

 

1910

305.7

1956

79

1911

168

1957

66

1912

75.5

1958

110

1913

311

1959

129

1914

135

1960

31

1915

38.1

1961

169

1916

54.5

1962

87

1917

63.3

1963

28

1918

102

1964

102

1919

20

1965

101

1920

156.6

1966

104

1921

175.6

1967

35

1922

49.4

1968

30

1923

142.3

1969

85

1924

140.9

1970

55

1925

57.1

1971

13

1926

50.1

1972

46

1927

77.7

1973

 

1928

45.6

1974

123

1929

138.1

1975

70

1930

55

1976

51

1931

177.8

1977

59

1932

101.9

1978

40

1933

77.4

1979

84

1934

114.7

1980

19

1935

132.6

   

1936

50.1

   

1937

111.3

   

1938

38.7

   

1939

167.8

   

1940

62.3

   

1941

     

1942

41

   

1943

41

   

1944

93.5

   

1945

69

   

1946

31.5

   

1947

54

   

1948

20.1

   

1949

39

   

1950

282.6

   

1951

     

1952

31

   

1953

     

1954

     

Table 3.22. Annual rainfall In millimetres, Tokar station.

1913

67

1960

10.8

1914

132

1961

248.4

1915

139.9

1962

57

1916

51.8

1963

200.2

1917

84.4

1964

75.4

1918

71.5

1965

117

1919

1966

68

 

1920

95

1967

102

1921

69

1968

59.5

1922

62 .1

1969

16

1923

64.3

1970

55

1924

111.7

1971

31

1925

87

1972

50

1926

45

1973

58

1927

46.5

1974

48

1928

SO

1975

96.7

1929

109. 3

1976

52

1930

41.7

1977

13.5

1931

22.7

1978

132.6

1932

9.7

1979

145.5

1933

38.9

1980

35.3

1934

8.5

1981

49.1

1935

8.6

1982

23.7

1936

124

1983

5.4

1937

 

1984

64

1938

 

1985

52.9

1939

9.3

1986

79.8

1940

28.3

1987

89.9

1941

}66.4

1988

92.7

1942

81.3

   

1943

161

   

1944

171.8

   

1945

33.8

   

1946

100.3

   

1947

50.2

   

1948

27.5

   

1949

42.2

   

1950

82.4

   

1951

144.7

   

1952

25.5

   

1953

44.9

   

1954

10

   

1955

51.6

   

1956

85.5

   

1957

165.5

   

1958

113

   

1959

44.5

   

 

Appendix 3.4. Annual rainfall z scores for 19 gauging stations in eastern


Figure 3.16. Annual rainfall z scores, 'Agig Station, 1921 to 1989.


Figure 3.17. Annual rainfall z scores, Arba'at Station, 1943 to 1987.


Figure 3.18. Annual rainfall z scores, 'Atbara Station, 1907 to 1988.


Figure 3.19. Annual rainfall z scores, Derudeb Station, 1944 to 1984.


Figure 3.20. Annual rainfall z scores, Erba Station, 1943 to 1981.


Figure 3.21. Annual rainfall z scores, Erkowit Station, 1943 to 1983.


Figure 3.22. Annual rainfall z scores, Gebeit Station, 1908 to 1980.


Figure 3.23. Annual rainfall z scores, Gebeit Mine Station, 1944 to 1981.


Figure 3.24. Annual rainfall z scores, Haya Station, 1940 to 1981.


Figure 3.25. Annual rainfall z scores., Kassala Station, 1901 to 1988.


Figure 3.26 Annual rainfall z scores, Muhammad Oul Station, 1953 to 1980.


Figure 3.27. Annual rainfall z scores, Musmar Station, 1948 to 1982.


Figure 3.28. Annual rainfall z scores, Port Sudan Station, 1941 to 1988.


Figure 3.29. Annual rainfall z scores, Sinkat Station, 1920 to 1982.


Figure 3.30. Annual rainfall z scores, Suakin Station, 1890 to 1988.


Figure 3.31. Annual rainfall z scores, Tahamyam Station, 1909 to 1980.


Figure 3.32. Annual rainfall z scores, Tokar Station, 1913 to 1988.

 

 

4. Drought, the market, and the impact of food aid in Red Sea Province, 1980 to 1989. Roy Cole

 

Summary

Drought-induced cereal price inflation and the consequent turning of the terms of trade against livestock was the principal mechanism identified in Red Sea Province that upset existing exchange entitlements and contributed to higher than normal mortality rates among the rural Beja populations. The present paper was written to synthesise data collected from several sources in the past with data collected by the Research Section at Oxfam Port Sudan.

The study had three objectives:

1. To examine market performance especially that associated with the famine in the mid-1980s in Red Sea Province.

2. To examine how the present inflationary period differs or resembles the early to mid-1980s.

3. To make statements regarding the benefits of free relief food distributions in the past and to evaluate the usefulness of continued free food deliveries in Red Sea Province.

The findings of the study are summarised below.

1. The terms of trade of cereals to goats turned largely to the detriment of those selling goats in 1984.

2. The terms of trade of cereals to livestock during the early 1980s seems to have not turned against sheep prices as they did against goat prices.

3. When free relief grain was made available in 1985 average cereal prices dropped by more than half (56%) and the terms of trade turned against cereals. This trend has been maintained to the present.

4. The terms of trade have been against cereals since 1986 but have dropped in favour of cereals since 1988 and are now levelling off.

5. Although free food deliveries seem to have been beneficial in reversing cereals price inflation in 1985 their benefit has diminished greatly as economic recovery has progressed. Those that still need some assistance, refugees and individuals marginalised by social circumstances should be assisted but on different terms from those used in the general feeding of the entire rural population of Red Sea Province.

 

Introduction

Since the Sahel drought of the 1970s analysts of drought and food stress have come a long way in the understanding of the mechanisms that contribute to food stress and mortality in Africa These economic, social, political, or environmental processes acting alone or together may originate from the local, national, or international levels or from a combination of levels. The present paper is concerned with one causal element of all the possible elements that could be examined: drought and price inflation.

Drought-induced cereal price inflation and the consequent turning of the terms of trade against livestock was the principal mechanism identified in Red Sea Province that upset existing exchange entitlements and contributed to higher than normal mortality rates among the rural Beja populations. The terms of trade of goats to sorghum declined from about one to one in the very early 1980s to about six to one in 1984 according to a report by Oxfam (1987). The present paper was written to as a result of new data collection since 1986 and is an attempt to synthesise those data collected in the past with the new data. The study has three objectives:

1. To examine market performance especially that associated with the famine in the mid-1980s in Red Sea Province.

2. To examine how the present inflationary period differs or resembles the early to mid-1980s.

3. To make statements regarding the benefits of free relief food distributions in the past and to evaluate the usefulness of continued free food deliveries in Red Sea Province.

The principal sources of data for the study were Oxfam Port Sudan files, the files of the Tokar Delta Board in Tokar town, and the Department of Agricultural Economics in the Ministry of Agriculture. The Oxfam data were collected by market clerks in the Derudeb and Tokar markets. The data were collected four times a month and, for the purposes of the present study, averaged by year. The Tokar Delta Board data are routinely collected monthly as part of a wider study on the prices of a variety of commodities in Tokar. These data will be presented for both markets below. Cereals prices will be discussed first, then livestock prices, and lastly both will be discussed together prior to the conclusion of the paper.

 

Drought and the market

Movements of prices probably are the most significant factor affecting the wellbeing and even the survival of the majority of people in the world today. Environmental variations such as drought change the relationship between marketed commodities through the production of relative scarcities and abundance. Sen (1981) demonstrated two entitlement relations that are affected by drought but have different relations to the market: direct and indirect entitlements.

A direct entitlement is best characterized farmers who produce the same good that they consume. These people do not have to enter the market to obtain their staple cereal. The herder, in contrast, with an indirect entitlement is obliged to enter into a market relation to get cereals. Sen identified three features of the indirect entitlement that make the impact of economic stress on pastoralists more significant than for farmers.

1. Cereals are cheaper nutrition at normal prices than livestock. In a situation of environmental stress demand shifts in that direction. Under ordinary circumstances the herder obtains cereal calories cheaply through the exchange of animals for grain. In situations of economic stress the herder is impelled to be even more dependent on cereals. This is why a drought that reduces both the animal stock and the grain output often leads to a decline in the terms of trade of livestock to cereals (Sen 1981).

2. Livestock for pastoralists are both production and capital. In periods of stress there is a "bigger burden of adjustment on animal supply to the market to meet the herdsman's grain demand as well as his other needs for cash" (Sen 1981: 110-111).

3. Consumption of the infinitely divisible and liquid cereal is more controllable than that of livestock.

In reality, pure pastoralists are rare. Most people who raise livestock have several occupations as a means of spreading risk. Most Beja in Red Sea Province farm as well as herd and engage in many other activities as well.

 

Cereals prices

The recent drought most commonly referred to in Red Sea Province occurred in 1982 and 1983 in the Tokar area when rainfall was well below the annual mean of sixty millimetres. In the populous interior areas of the province the worst years were 1983 and 1984 where, for example, in the agriculturally important Khor Arab basin there were no floods for both years.

The following figure presents prices for four cereals in the Tokar market: three types of sorghum, Feterita, Hijiri Gedarif, and Hijiri Tokar and one millet.


Figure 4.1. Annual prices for four cereals, Tokar market, 1981 to 1989.

From 1981 to 1989 average prices in Tokar for the four cereals presented above rose 684% from 22.8 to 156 Sudanese pounds per 100 kilogram sack. Within this trend there are two peaks and two troughs. More properly speaking, perhaps the peaks should be called one peak and one plateau rather than two peaks. Although it is too early to tell how 1989 will turn out, our data for 1989 run to August, and prices should fall after harvest near the end of the year. Because of this uncertainty, what appears now to be a 1988-89 plateau may well be a peak. However that may be, the first peak in our present dataset was in 1984. From 1981 to 1984, cereals prices rose 346%, from 22.8 to 79 Sudanese pounds per 100 kilogram sack. Cereals prices dropped 56% in 1985 and 1986, almost to their 1983 levels then rose 457% in a second peak from 1988 to the present, from 34 to 156 Sudanese pounds per sack.

The figures for Derudeb Town present a partial but much the same story as the Tokar market. The two cereals for which we have data are Feterita and Mugud Gedarif sorghum. The increase in the average price of these two sorghums from 1986 to 1989 was 249%, from 38.8 to 96.9 Sudanese pounds per 100 kilogram bag. Some caution should be exercised with the Derudeb data because the 1989 dataset has only one month's observation. The actual difference is probably higher because the observation that we have is from not long after the harvest of 1988 and prices generally rise between harvests.


Figure 4.2 Prices for hero cereals, Derudeb Market, 1986 to 1989.

It is important to place changes in cereal prices in the context of changes in two other commodities: cash crops in Tokar and sorghum in Gedarif, the principal source area for cereal imports into Red Sea Province. The figure below presents the prices of a cash crop from the Tokar market Egyptian beans (ful masry). Interestingly, the Egyptian bean price changes exhibit an upward curve of constantly inflating prices quite different from that of cereals prices in the same market. Prices since 1987 have risen further although we do not have figures from the Tokar market.


Figure 4.3. Ful masry prices In Tokar market.

There is much mechanised rainfed cereal production in the Gedarif area. It is one of the few surplus producing areas in the Sudan. Cereals from Gedarif are readily available in all Red Sea Province markets and make up shortfalls in local production. The following figure presents the prices for Feterita sorghum in the Gedarif market from 1970 to 1988.


Figure 4.4. Feterita prices, Gedarif market 1970 to 1988.

The Department of Agricultural Economics of the Ministry of Agriculture estimated (1988) that after the excellent crop year of 1986 in the Gedarif area cropped area declined 71% for several reasons:

1. The low prices received by farmers in 1986 discouraged them from planting more.

2. Low and unevenly distributed rainfall and late plantings.

3. Pest infestations.

4. Unavailability of engine oil at planting time for mechanised agriculture.

The Department of Agricultural Economics (1985) found that the 1984 and 1985 seasons were affected by drought, particularly in Gedarif. Only a third of the planted areas were harvested in 1985 and prices were highest during that year. On the area that was harvested yields were below average.

It is interesting to compare the cereal prices in the Tokar market with those from Gedarif, a major source of imported grain for Red Sea Province, to show that production outside Red Sea Province had little to do with the fall in cereal prices in Red Sea Province from 1985 to 1987. The free food deliveries beginning in early 1985 in Red Sea Province had a significant impact on cereal prices and was the principal factor behind the drop in cereal prices after the drought-related inflation of 1983 and 1984. The Gedarif market, in contrast, had exceedingly poor performance in 1984 and 1985 and prices were rising during this period. The Red Sea Province prices began falling a full year before those of Gedarif did so.

 

Livestock prices

The key to understanding food stress in Red Sea Province is not the price of cereals alone but the price of cereals in relation to other commodities that may be exchanged for cereals. Under ideal circumstances we would have to take into account the change in value of wage labour, sharecropping arrangements, charcoal, firewood, and other rural products, handicrafts, and livestock because few people in the rural areas of Red Sea Province herd livestock exclusively as an occupation. Most people have several occupations: cereals cultivation, vegetable cultivation, cotton cultivation, wage labour migration, fuel production, handicrafts, bush food collection, et cetera. Many are involved with the religious establishments of Hamashkoreb and Tumaala, located in southcentral and northcentral Red Sea Province respectively, where nationally and internationally-connected social support mechanisms have developed to cushion food stress. We have only data for livestock value and, consequently, our conclusions must be limited and tentative.

The following figures present prices for goats and sheep by sex and age class at the Derudeb town market and milk prices for the Tokar market.


Figure 4.5. Annual prices of male goats, Derudeb Market, 1980 to 1989.


Figure 4.6. Annual prices of female goats Derudeb Market, 1980 to 1989.


Figure 4.7. Annual prices of male sheep, Derudeb Market, 1980 to 1989.


Figure 4.8. Annual prices of female sheep, Derudeb Market, 1980 to 1989.

 

Cereals and livestock price changes

The following figures illustrate the relation between average prices for small stock and cereals prices from 1980 to the present.


Figure 4.9. Annual average goat and cereal prices, Tokar and Derudeb markets, 1980 to 1989.


Figure 4.10. Annual average sheep and cereal prices, Tokar and Derudeb markets, 1980 to 1989.


Figure 4.11. Cereals to livestock price ratios, Tokar and Derudeb markets, 1981 to 1989.

 

Conclusion and discussion

Judging from the available data and with all the caveats that such data warrant, four statements may be made by way of a conclusion.

1. The terms of trade of cereals to goats turned largely to the detriment of those selling goats in 1984. This was probably due to two factors acting in tandem to exacerbate what might otherwise have been a local crisis.

A. Local drought and harvest failure in 1983 and 1984 in the important interior grain producing districts of Red Sea Province.

B. Harvest failures elsewhere in the Sudan such that the Red Sea Province deficits could not have made up through the market mechanism. The extent of the harvest failures throughout the Sudan during this period contributed to the food stress experienced by many people in Red Sea Province during the mid-1980s.

2. The terms of trade of cereals to livestock during the early 1980s seems to have not turned against sheep prices as they did against goat prices. The reasons for this are unclear. It may simply be due to the fact that sheep are more expensive than goats (see Hassan Mohammed Salih 1976) or it may be due to any one or all three of the following factors.

A. Because of the extreme annual variation in forage availability in southcentral and southwest Red Sea Province sheep are naturally scarce except for the rainy season.

B. High sheep mortality against relatively low goat mortality during the drought of 1983-1984. Sheep are much less resistant to stress than are goats.

C. The nature of sheep as a preferred commodity relatively immune from market price collapse. Goats are the liquid currency of trade in Red Sea Province. Sheep are a specialty product raised for export to the towns and to Saudia Arabia. The high prices paid for male sheep reflects the high demand and value associated with their use in religious ceremonies three times a year.

3. When free relief grain was made available in 1985 average cereal prices dropped by more than half (56%) and the terms of trade turned against cereals. This trend has been maintained to the present.

4. The terms of trade have been against cereals since 1986 but have dropped in favour of cereals since 1988 and are now levelling off. The reasons behind this change probably lie at the national and international levels rather than the local level and are related to the devaluation of the Sudanese pound and the general and extreme commodity price inflation that has occurred since the early part of 1988.

Although one would normally expect cereal prices to drop after the unprecedented harvest of 1988 they have not done so. There is an explanation for this that goes some way in resolving the sluggish response of the market: commercial producers are storing their cereals to sell at a later date and small producers are storing their harvest as a security measure. In any case, the alarmingly high cereal prices and the declining terms of trade against livestock deserves watching. People who do not farm and those who have few or no livestock are at risk. Particularly vulnerable are households headed by women in rural areas. They may not have been able to build up assets when the terms of trade were overwhelmingly against cereals.

 

The impact of the July change in government on livestock prices

There has been no price control on cereals in the Sudan since the change in government of 30 June, 1989 with the exception of a short period when price controls were placed on relief food in the Derudeb area. The new government is controlling the inter-provincial movements of cereals and had forbidden the export of cereals. An attempt has been made to control livestock and meat prices. The cheapest available meat in Port Sudan, beef, was brought down 30 Sudanese pounds per kilogram, from 50 to 20 £S per kilogram, in early July. Since early July price ranges, minima and maxima, have been set for livestock by age class. In November price controls were imposed on milk in Port Sudan. There may be negative effects felt by producers of sheep for the religious holiday markets although it is difficult to judge how important this will be to the general economy.

 

Comments on continued general free food distribution

Are there any arguments for the continued distribution of free food aid in Red Sea Province? The answer is yes and no. Yes to a social security type assistance and no to a general free food distribution. The majority of people in Red Sea Province do not need food aid. Those who do need continued assistance are refugees and divorced women and widows with dependent children (see Cole and Cole, Nutritional status of children in Red Sea Province, November 1985 to November 1987, below). The refugees are principally Beni 'Amer, or Habaab who transhume from the coastal areas of South Tokar and the Tokar Delta to the Eritrean highlands. Those who are not Beni 'Amer are found generally in the camps near Garora. The Beni 'Amer, because their population is split between the Sudan and Eritrea, have been able to reside in the Sudan as Sudanese. The closure of the Sudanese-Eritrean border and the mining of the area behind the border in the early 1980s had much to do with their present position. They were trapped in the Sudan for several dry seasons. Their animals were sold or died. When the EPLF took control of the border areas these people were assetless. Most of them remain in the Sudan today. Those in the camps are the "real" refugees supported by the United Nations High Commission for Refugees (UNHCR). The hidden refugees are the Beni 'Amer and the Habaab.

Knowing as we do that most people have more than one occupation as a risk minimising strategy recovery from drought assumes a different perspective than that it possessed several years ago when NGOs believed that the only significant occupation of rural people in Red Sea Province was herding livestock and that income from the towns did not return to the rural areas5. However, those people who possessed livestock after the drought of 1983-84 have had several good years in which to recover their assets through employment in the urban or rural areas and through the natural reproduction of their animals. The best years have been the last two. The terms of trade of cereals to small stock have been extremely favourable to the animal owner as well. Most of those people who were unfortunate enough to have some of their livestock due to drought in 1983 and 1984 have gone to the towns and/or have taken up other occupations. According to a report by the Environmental Research Group Oxford (ERGO), currently doing an aerial survey of livestock and human population in and around Red Sea Province, there is already a drift from the town to the country. This same group of researchers also maintain that the majority of people in Red Sea Province live in towns and not the countryside. The implication of their finding is that people are accumulating assets in the urban areas, investing in livestock, and then seasonally returning to the country. It is likely that these people have strong linkages both the urban and rural areas and if they did not have a foot in both the urban and rural areas before the drought, they have such a position now. The dichotomy between urban and rural is not absolute in Red Sea Province just as it is not absolute anywhere else in the world. The urban and the rural coalesce in such towns as Derudeb, Sinkat, Tokar and Haya and places in Port Sudan such as Daym al-'arab, Hai Walli, Daym al-wuhda, and Ongwob where goats and sheep are more numerous than people and camels more populous than automobiles. There is a constant drift and exchange of people and products between these places, rural Red Sea Province, the rest of the Sudan, and the world. It seems that a more targeted approach is needed to help marginalised people in Red Sea Province and that the urban countryside, quarters like Daym al-'arab and towns like Derudeb, may be the best places from which to begin assisting the rural areas.

 

Limitations of the study

There was no way to validate independently the data collected by the market clerks and the Tokar Delta Board. The clerks and the Board take the average figure for the cereals and animals presented at the market. How well they followed this method is not known. Caution should be exercised in interpreting data from one market in conjunction with another. Because so little is known about market performance around the Sudan we do not know how appropriate it was to examine cereals prices from one market in conjunction with livestock prices from another.

 

References

Department of Agricultural Economics. (1988) Agricultural Situation and Outlook, 4(2). Ministry of Agriculture and Natural Resources, Khartoum.

Department of Agricultural Economics. (1985) Agricultural Situation and Outlook annual report 1984-85. Ministry of Agriculture and Natural Resources, Khartoum.

ERGO (1989) Integrated livestock surveys of Red Sea Province, Sudan. Preliminary report of Phase One aerial and ground survey, February-April 1989. Environmental Research Group Oxford, Oxford.

Mohamed Farah, A. A. and El Saeed, H.R. (1985) Agricultural prices in Sudan: a historical review and analysis, 1970 - 1984. Marketing Section Department of Agricultural Economics, Planning and Agricultural Economics Administration, Ministry of Agriculture and Natural Resources, Khartoum.

 

 

5. Nutritional status of children in Red Sea Province, November 1985 to November 1987. Mary Cole and Roy Cole

 

Summary

The nutritional surveillance teams at Oxfam Port Sudan undertook six province wide tours of Red Sea Province between November 1985 and November 1987. Weight for height measurements were taken on approximately 2000 children less than or equal to 115 cm in height during each tour (cycle). The present study is a reanalysis and a synthesis of the data collected during this time.

In Red Sea Province as a whole, the nutritional status of children <=115 cm in height improved significantly between cycles 1-3 inclusive and 4-6 inclusive (approximating 1986 and 1987). Female children had a marginally better mean percent weight for height than male children in 1987, but equal proportions of males and females were malnourished (less than 80% reference median weight for height) in both cycles 1-3 and 4-6. Significantly more females than males were severely malnourished in cycles 13 (less than 70% reference median weight for height). There was a significantly higher proportion of males than females in the sample in cycles 13 and 4-6. Unfortunately we lack mortality data and details of refusal rates by sex which would be required to interpret these results. The percentage of the sample less than 75 cm in height increased significantly between cycles 1-3 and 4-6.

At the district level, Rural Port Sudan and North Tokar Districts had a percentage of malnourished children which was lower than the province wide average in 1986. Halaib District had a percentage of malnourished children that was equal to the province wide average in 1986, and Derudeb, Haya, Sinkat and South Tokar Districts had a percentage of malnourished children that was above the province wide average in 1986. Between cycles 1-3 and 4-6, the nutritional status of children in Rural Port Sudan and North Tokar did not change. The nutritional status of children in the remaining districts improved significantly between cycles 1-3 and 4-6, with the important exception of Haya District. The poor nutritional status of children in Haya District remained unchanged between cycles 1-3 and 4-6. This was particularly alarming because it has been estimated that up to 28% of the total population of the province live in Haya District for all or part of the year.

The highest rates of malnutrition were found in children less than 75 cm in height. This approximates to children less than one year of age. These results should be interpreted with caution, however, because the majority of these children were measured upright rather than supine, a technique which has not been validated. In children over 75 em in height, highest rates of malnutrition were found in the height category 75.1-85 cm. This corresponds to weaning age. The poor nutritional status of breast fed babies raises concerns about maternal health and nutrition during pregnancy and lactation. Children of weaning age are at high risk of malnutrition also. More information is needed about infant feeding practices and weaning in Red Sea Province.

Seasonal changes in nutritional status were apparent in both cycles 1-3 and 4-6. Children had the worst nutritional status in August and September, at the end of the dry summer season with the associated lack of cereals, grazing and milk. Children had the best nutritional status in January, after the harvest and when grazing and milk production had improved. By district, Halaib and Rural Port Sudan Districts did not show such seasonal trends in nutritional status. These districts are in the north of the province and have low rainfall with little seasonal variation. Seasonal variations in nutritional status should be considered when comparing the results of surveys undertaken at different times of the year.

Children who were living in settlements described as camps had a significantly worse nutritional status than children living in railway towns, towns or rural areas in 1986. By 1987, however, there was no significant difference in the nutritional status of children in any of the settlement types.

There was no correlation between the mean relief grain ration per family per day by settlement and the mean percent weight for height of children by settlement. This may be a reflection of the limitations of the analysis, which were imposed by the methods of data collection by both the Relief Section and the nutritional surveillance teams. Improved coordination between the Relief section and nutritional surveillance teams must be a priority in the future if nutritional surveillance data are to contribute to relief allocations in a meaningful way.

The smallest unit of analysis (the settlement) explained 12.9% of the variation in percentage weight for height found in cycles 1-6. It is likely that of those variables measured the individual settlement is the single most important factor in determining the nutritional status of children. The practical implications of this finding are that as many settlements as is practical should be sampled during nutritional surveillance in order to obtain an accurate picture of the nutritional status of children, and research into the causes of malnutrition in Red Sea Province should focus on the settlement.

The Ministry of Health of the Sudan government, together with USAID, undertook a survey of the nutritional status of children under five years of age in Northern Sudan during 1986 and 1987. These surveys found that children in Red Sea Province had a consistently higher nutritional status than had been found in the Oxfam surveys. This was probably because the government surveys included urban areas, which were excluded from Oxfam surveys. The results of the government surveys confirmed Oxfam findings with respect to the high risk of malnutrition in weaning age children, and the importance of the settlement in explaining variation in nutritional status.

After an initial phase of famine relief, the emphasis of relief efforts in Red Sea Province has been on a general concept of recovery rather than on nutritional interventions per se. Because of the alarming rates of malnutrition in babies and children of weaning age, pregnant and lactating women and children of weaning age should be targeted with specific interventions aimed at improving their health and welfare. This will involve examining the nutritional value of the relief ration, and developing new methods of targeting and monitoring. This should become primarily a gender issue. Oxfam should encourage innovative approaches to nutritional surveillance in the field in order to develop methods of assessment which are acceptable to the Beja, and locally appropriate standards for nutritional status which could be used in conjunction with internationally accepted standards. Methodological issues which have been raised as a result of practical experience should be addressed promptly and incorporated into guidelines which could be used in the event of future relief efforts in Red Sea Province.

 

Introduction

The present study is a reanalysis and a synthesis of the nutritional surveillance data collected by Oxfam Port Sudan from November 1985 to November 1987. The purpose of the study was to bring together data from six province-wide cycles of nutritional surveillance to provide an overview of the nutritional status of children in Red Sea Province, particularly with reference to significant changes over time and between different areas of the province. At the same time, a more detailed analysis of the data than had previously been undertaken was required to more accurately characterize malnutrition for future targeting and programme planning. This study also forms the basis for comparison with the nutritional status of children in Red Sea Province collected in 1989. These results are presented as a supplement to the present report. The following work was completed as part of a 90 day consultancy between June and November 1989, and in collaboration with the research section, Oxfam Port Sudan.

 

Methods

1. Methods used in the original nutritional surveillance.

This is not intended as an exhaustive review of the methods used in cycles 1-6, nor as a critique. Rather, it is intended to provide a framework within which to assess the results. A description of methods used and an assessment of the practical experiences of the nutritional surveillance teams in the field is planned for early 1990 (Fatima Gebreil).

a. Sampling.

The population targeted for surveillance was children in Red Sea Province less than or equal to 115 cm in height who were receiving food aid. The unit of comparison was the administrative district. The sampling frame was drawn from World Food Programrne/Oxfam lists of settlements receiving food aid, and included the number of families estimated to be associated with that settlement for the purpose of receiving food aid. Each of the seven administrative districts in Red Sea Province was surveyed every four months. Each four month province-wide survey was called a cycle. Six cycles were completed between November 1985 and November 1987.

The method of selecting the sample size varied for cycles 1 and 2. An attempt to weight the sample by district population from the 1983 census was abandoned. From cycle 3 onwards the sample size (n) was derived from a 95% confidence interval for an estimated percentage of malnourished children (p) of 22%, and with a precision of +/- 5% for the estimate of change.

C.I. = p ± 2 {p(100-p)/n}

This resulted in a sample size of 275 for each unit to be compared (the district). Because the proportion of the population to be sampled was small, it was assumed that the sample was drawn from an infinite population, and no correction factor was applied for actual population. The same number of children were therefore surveyed in each district, except in South Tokar, where the sample size was increased to 370 because it was considered to be densely populated.

The sample was divided into clusters of 30 children, a number selected as being both the number of children who could be measured in one day, and the minimum number required to be representative of the total settlement. The required number of children would therefore be selected from approximately nine settlements (12 in South Tokar). These were randomly selected from the lists for each district, after first being weighted for the number of families in each settlement. Settlements in the South Tokar mountains were excluded from the list because of inaccessibility. The sampling procedure was altered in cycle 6 because of complaints of excessive numbers of repeat visits. The majority of those settlements sampled in cycle 5 were excluded from the lists from which the random selection of the settlements to be visited in cycle 6 were made. The selection for cycle 6 was not therefore strictly random.

b. Sampling in the field.

After arriving at each selected site, the team leader met with the local community leader (shaykh) and mapped the approximate locations of the distinct clusters which made up the total settlement. These were then numbered, and another team member not involved in the mapping asked to choose a number. This was the cluster visited. In the majority of cases there would not be 30 children in the cluster, and the selection procedure would be repeated until 30 children had been measured. In larger clusters, individual houses were selected and all the children in them measured until the required number had been reached. Another technique involved collecting all the children in a central location before selecting and measuring them. It is possible that the technique used depended on the receptiveness and cooperation of the shaykh, and that house to house visits may not have been acceptable in some areas. This will be discussed in more detail in the pending discussion of field experiences.

c. Measurement techniques.

Children were weighed to the nearest 0.1 kg using Salter hanging scales. The scales were calibrated using 1, 5 and 10 kg weights at the start of each weighing session. Stales were replaced after a maximum of two cycles, or whenever required. The scales were held by one female team member while the child was weighed by another. Very small children were suspended in a nylon sling, while older children held onto the balance. Children were not required to remove light clothing.

Height or length was measured to the nearest 0.1 cm using a locally made board with a metal tape attached, and with a sliding head board. Children who were too young to stand upright, or who were too weak, were measured lying down. There were no quarditative cut off points for a length versus height measurement; In many cases mothers objected to young or weak children being laid horizontally, a position associated with being laid out after death. These children were supported in a vertical position against the height board.

Sex, height and weight, together with comments on the child's condition (fever, marasmus, other illness, etc.) were recorded on prepared forms (Appendix 5.1). Children with oedema were marked as having kwashiorkor, and their weight for height set at less than 7096 irrespective of the actual measurements.

d. Analysis.

Raw data were brought back to the office for analysis. Percent of median weight for height or length was calculated for each child, using the NCHS/CDC/WHO normalized reference of February 1982, taken from "Refugee Community Health Care" (Ed S.Simmonds, P.Vaughan and S.W.Gunn; Oxford University Press, Oxford 1983). Mean percent weight for height, percent less than 80% weight for height, and percent less than 70% weight for height were calculated for each settlement and for each district. Hand calculators were used throughout.

e. Reporting.

Cycles one to five were written up as individual reports and circulated to the Relief Section of Oxfam Port Sudan, Oxfam Khartoum, the Sudan Desk and Health Unit Oxfam House. Raw data and district summaries were made available on request to the Relief Section in Port Sudan.

2. Methods used In the present study.

The present study is a reanalysis and a synthesis of the nutritional surveillance data collected from cycles 1 to 6. The original raw data were entered into a spreadsheet. For each case the following variables were recorded:

1. Case number.

2. Cycle number.

3. District.

4. Health status of child (good/bad).

5. Height of child.

6. If height or length of child were measured.

7. If child's age was less than one year (mothers' report).

8. Month of survey.

9. Settlement name.

10. Sex of child.

11. Weight of child.

12. Year of survey.

These variables were collected in the original surveys. The variables "less than one year by mothers' report" and "health status" were subsequently dropped because of poor quality and inconsistent reporting, particularly in the later cycles. In addition to the above variables, new variables were added:

1. Average daily ration of relief grain per family.

2. Ecozone.

3. Food security zone.

4. Season.

5. Settlement type.

The classifications used for each variable are given in Appendix 5.2. The first three additional variables were based on a mapping of all the places surveyed in cycles 1-6. Based on latitude, longitude and the major khor system with which it was associated, each settlement was placed within an ecozone. These were taken from Watson's 1976 aerial survey of livestock and human population in Red Sea Province (Appendix 5.3). A season (major wet, minor wet, dry and harvest) was assigned to each ecozone by month (Appendix 5.4). A season was then assigned to each case according to ecozone in which the settlement was located and the month of the survey. "Food security zone" refers to a classification of Red Sea Province carried out by the Research Section, Oxfam Port Sudan, in which zones of high, medium and low drought impacts and food insecurity were identified based on a composite of variables that included rainfall, floods, agriculture, livestock, grazing and economic opportunities (Appendix 5.5). Settlement type was either railway, town, rural or camp. The average ration of grain delivered per family to each settlement was calculated from Oxfam and W.F.P. distribution schedules. Actual quantities and days between deliveries were used rather than allocated quantities and proposed delivery dates. The figure calculated represented the average amount of grain per day delivered to each family for the distribution cycle during which the nutritional surveillance took place. The limitations of this calculation are discussed below.

After completing the data set as outlined above, sex specific percent weight for height/length and z-scores were calculated for each case using WHO/NCHS/CDC references taken from "Measuring change in nutritional status" (WHO 1983). These tables were entered on the spreadsheet and the calculations made using the "Lookup" function. Percent weight for height and z-scores were rounded to two and three decimal places respectively. Each case was coded as being in one of seven height categories and eight percent weight for height categories.

Height categories:

Approximate age equivalent:

<= 55.0 cm

< 3 months

55.1 - 65.0 cm

up to 6 months

65.1 - 75.0 cm

6-12 months

75.1 - 85.0 cm

1-2 years

85.1 - 95.0 cm

2-3 years

95.1 - 105.0 cm

3-4 years 3 months

105.1 - 115 cm

>4 years 3 months

Percent weight for height categories:

<

 

60

60

-

69.9

70

-

79.9

80

-

89.9

90

-

99.9

100

-

109.9

1 10

-

1 19.9

>=

 

120

The data set was then edited by sorting on z-scores and rechecking extreme values with the raw data. Spot checks were also made through the rest of the data. Because of the size of the data set (over 14000 cases and 250000 individual pieces of data), all character based variables such as district and settlement names were converted to numbers, and a code book developed. The data set was then converted to an American Standard Code for Information Interchange (ASCII) file for reading into a statistics package. Copies of the raw data in ASCII format and the code book are available on request.

Although z-scores are a more accurate measure of nutritional status than percent weight for height, percent weight for height is the measure presented in this report. Percent weight for height was chosen because of a general unfamiliarity with the concept of z-scores, unfamiliarity with the relation of z-score cut off points to degrees of malnutrition, and because percent weight for height has historically been the measurement of choice in reporting nutrition surveillance data in Red Sea Province.

The data set was divided into two groups; children 75 cm and under, and children 75.1115 cm. The 75 cm cut off point was selected as approximating the height of a one year old. A height cut off was selected because mothers' reporting of children as being under one year old was inconsistent, particularly in the later cycles. After examining the raw data, and the heights/lengths of children who were recorded as being under one by mothers' report in the early cycles, the WHO recommended cut off of 80 cm for one year olds seemed inappropriately high for this sample. The division of the sample into those less than and equal to or more than 75 cm was carried out for three reasons:

1. Children under one year old tend to be breast fed. Their nutritional status is therefore not as reflective of the food stresses faced by a community as the nutritional status of weaned children, and should be reported separately.

2. There are some technical problems with the data collected on children less than one year old:

a. Sampling of under one year olds may not have been consistent. The policy as to whether children under one should be included in the sample changed between cycles 1 and 2. After cycle 1, any child selected who was less than one year old by mothers' report was measured, but another child more than one year old was added to the sample to make up a quota of 30 children over one year old. The intention was to report the nutritional status of less than one year olds separately, but reports from cycles 1-5 appear to include all children under 115 cm. In the later cycles the sample was restricted to 30 children irrespective of whether they were less than or more than one.

b. A large number of under one year olds were measured in a vertical position, being supported by a team member. It has not been possible to validate this procedure.

The sampling method used in cycles 1-6 had the district as the unit of analysis. The same number of children were sampled in each district. In order to obtain representative provincewide statistics, it was necessary to weight each district statistic by the proportion of the total population of Red Sea Province in that district. These population proportions were obtained from the Oxfam/ERGO 1989 low level aerial survey of Red Sea Province. These were considered the most accurate population data avail-able at the time of the analysis. Figures for population density and inhabited area of each district were taken from the March 1989 survey. This was considered to be when the population was at its' annual peak. Population per district was obtained by multiplying population density per square kilometre by habitable area in square kilometres. Uninhabited areas of Halaib and Haya Districts were excluded from the total area of those districts. In addition, 25,000 square kilometres were excluded from South Tokar District. This was the estimated area of the mountain zone, which was not included in the sampling frame for cycles 1-6. The percentage of population per district was then used as a weighting factor for district statistics when being summed to arrive at province wide figures (Table 5.1). In applying these weighting factors to data from earlier years, the assumption was made that despite population growth, the proportions of the population in each district have not changed significantly.

Table 5.1. Population densities, inhabited area and proportion of population per district, Red Sea Province.

DISTRICT

POP/KM

AREA (KM )

POP

%POP

DERUDEB

2.47

12100

29887

10.1

HALAIB

0.59

29100

17169

5.8

HAYA

3.33

25200

83916

28.4

N.TOKAR

2.18

19300

42074

14.2

R.P.S.

4.93

15800

77894

26.3

SINKAT

3.39

7900

26781

9.0

S.TOKAR*

5.07

3600

18252

6.2

* Coastal strip only (excludes mountains).

Source: ERGO, Preliminary report of phase one aerial and ground survey, February April 1989.

In addition to cycle by cycle results, annual averages were calculated in order to make comparisons of change over time without the influence of intervening variables such as season. Cycles 1-3 and cycles 4-6 were averaged to correspond approximately to 1986 and 1987 respectively.

Statistical analysis was carried out in two statistical packages; Systat and SPSS-PC+. Significance testing was limited to simple l-tests for comparing two means, ANOVA for comparing groups of means, and confidence intervals to compare proportions. The relationship between the relief ration and percent weight for height was examined using Spearman's rank correlation. A 95% confidence level was used throughout; results were considered significant only if there was less than a 5% probability they could have occurred solely by chance.

 

Results

1. Timing and location of Oxfam Port Sudan Nutritional Surveillance.

Table 5.2. Timing of Oxfam Nutritional Surveillance Cycles 1-6.

         

CYCLE BY MONTH

YEAR

J

F

M

A

M

J

J

A

S

O

N

D

1985

                   

1

1

1986

1

1&2

2

2

2

2

3

3

3

3

3

4

1987

4

4

4&5

5

5

5

5

6

6

6

6

 

The average time taken to survey the whole province was four months. Three surveys were completed in 12 months. Cycles 1 and 4, 2 and 5, and 4 and 6 were carried out at comparable times of year (Table 5.2). Within each cycle, the order in which the districts were visited varied (Table 5.3). The locations of the sites sampled in cycles 1-6 are shown in Appendix 5.6.

Table 5.3. Districts visited by monfh, NST cycles 1-6.

     

MONTH BY CYCLE

DISTRICT

1

2

3

4

5

6

DERUDEB

NOV

MAR

SEP

JAN

MAY

SEP

HALAIB

JAN

JUN

OCT

JAN

JUN

OCT

HAYA

DEC

APR

AUG

DEC

MAR

SEP

N.TOKAR

JAN

MAY

OCT

DEC

MAY

OCT

R.P.S.

JAN

JUN

NOV

MAR

JUL

DEC

SINKAT

DEC

APR

SEP

DEC

APR

OCT

S.TOKAR

JAN

MAR

SEP

JAN

MAR

OCT

Table 5.4. Total number of visits and number of places visited by district, cycles 1-6.

DISTRICT

NUMBER OF

NUMBER OF

% VISITED

% VISITED

 

VISITS

PLACES

> ONCE

3 TIMES

DERUDEB

57

37

35

13.5

HALAIB

75

47

45

13

HAYA

77

53

38

7.5

N.TOKAR

72

37

62

19

R.P.S.

67

49

29

8

SINKAT

79

55

35

9

S.TOKAR

77

47

43

17

TOTAL

504

325

40

12

Oxfam received many complaints from community leaders of repeat sampling and excessive visits by nutritional surveillance teams. Table 5.4 shows the total number of visits made to each district over cycles 1-6, together with the total number of different places visited. Over all cycles (two years), 40% of places visited were visited more than once, and 12% of places visited were visited three or more times. The maximum number of times any place was visited was four times.

2. Description of the sample.

a. Sample size

Sample sizes by district and cycle for children 75.1-115 cm and <75 cm are shown in Tables 5.5 and 5.6 respectively.

Table 5.5. Sample sizes (children >75 cm) by cycle and district.

 

CYCLE

DISTRICT

1

2

3

9

5

6

1-3

4-6

DERUDEB

169

322

258

211

195

189

749

595

HALAIB

264

324

231

203

190

190

819

583

HAYA

150

337

252

277

258

248

739

783

N.TOKAR

330

324

257

255

224

232

911

711

R.P.S.

214

327

266

252

264

254

807

770

SINKAT

227

338

257

293

267

262

822

822

S.TOKAR

301

323

241

291

292

279

865

862

TOTAL

1665

2295

1762

1782

1690

1654

5712

5124

Table 5.6. Sample sizes (children <75 cm) by cycle and district.

 

CYCLE

DISTRICT

1

2

3

4

5

6

1-3

4-6

DERUDEB

22

34

42

35

46

51

98

132

HALAIB

66

44

56

41

53

57

166

151

HAYA

30

33

49

53

75

86

112

2;4

N.TOKAR

89

41

44

53

77

70

174

200

R.P.S.

26

41

35

52

96

76

102

224

SINKAT

40

40

44

65

66

68

124

199

S.TOKAR

88

46

59

70

70

81

193

221

TOTAL

361

279

328

369

481

489

968

1339

The percent of the total sample which comprised children less than or equal to 75 cm by district and cycle is shown in Table 5.7. For Red Sea Province as a whole there was a significantly higher percentage of children less than 75 cm tall in cycles 46 than in cycles 1-3. At the district level there was a significantly higher percentage of children less than 75 cm tall in cycles 4-6 than in cycles 1-3 for all districts except Halaib and South Tokar.

Table 5.7. Percent of sample <75 cm by cycle and district.

 

CYCLE

DISTRICT

1

2

3

4

5

6

1-3

4-6

DERUDEB

11.5

9.6

14.0

14.2

19.1

21.3

11.6

18.2**

HALAIB

16.7

8.7

15.6

15.3

23.5

23.5

16.9

20.6

HAYA

16.7

8.9

11.2

16.1

22.5

25.7

13.2

21.2**

N.TOKAR

21.2

11.2

14.6

17.2

25.6

23.2

16.0

22.0**

R.P.S.

10.8

11.1

11.6

17.1

26.7

23.0

11.2

22.5**

SINKAT

15.0

10.6

14.6

18.2

19.8

20.6

13.1

19.5**

S.TOKAR

22.6

12.5

19.7

19.4

19.3

22.5

18.2

19.5

TOTAL

17.9

10.8

15.7

17.2

22.2

22.8

14.5

20.7**

** Significant difference between cycles 1-3 and 4-6 (p<.05)

b. Proportions of males and females in the sample.

The ratios of males to females by district and cycle for children greater than 75 cm and less than or equal to 75 cm are shown in Tables 5.8 and 5.9 respectively.

Table 5.8. Ratios of males:females (children >75 cm) by cycle and district.

 

CYCLE

DISTRICT

1

2

3

4

5

6

1-3

4-6

DERUDEB

1.06

1.37*

1.10

1.22

1.44*

1.33

1.20*

1.32*

HALAIB

0.89

0.98

0.94

0.88

1.18

0.96

0.94

1.00

HAYA

1.14

1.13

0.97

1.16

0.97

1.25

1.08

1.12

N.TOKAR

1.17*

1.13

1.14

0.92

1.20

1.17

1.15*

1.08

R.P.S.

1.55*

1.14

1.53*

1.17

1.28*

1.17

1.36*

1.21*

SINKAT

1.39*

1.28*

0.85*

1.02

1.09

1.02

1.15*

1.04

S.TOKAR

1.01

1.07

0.94

1.12

1.20

1.05

1.01

1.12

TOTAL

1.14*

1.15*

1.05

1.07

1.18*

1.13*

1.12*

1.12*

* Significantly different from 1.00 at p=.05

In the sample 75.1-115 cm, there was a significantly higher proportion of males than females for the whole province in both cycles 1-3 and 4-6. By district, Derudeb and Rural Port Sudan had significantly higher proportions of males than females in both cycles 1-3 and 4-6, while North Tokar and Sinkat districts had significantly higher proportions of males than females in cycles 1-3 only.

Table 5.9. Ratios of males:females (children <75 cm) by cycle and district

 

CYCLE

DISTRICT

1

2

3

4

5

6

1-3

4-6

DERUDEB

0.83

0.62

0.68

0.75

0.92

1.09

0.69

0.91

HALAIB

0.89

0.63

0.60

1.73

1.04

0.68

1.71

1.01

HAYA

1.50

1.06

0.88

1.04

1.08

0.95

1.07

1.02

N.TOKAR

0.98

1.28

1.00

1.41

0.97

1.19

1.04

1.15

R.P.S.

1.36

0.78

1.19

1.36

1.13

1.24

1.04

1.22

SINKAT

1.00

1.35

1.39

0.81

0.83

0.74

1.24

0.79

S.TOKAR

1.26

0.92

0.97

0.89

1.50

1.08

1.08

1.13

TOTAL

1.07

0.91

0.91

1.07

1.06

0.98

0.97

1.03

Despite some apparently large differences between the proportions of males and females less than 75 cm, none were significantly different from a ratio of 1.00 (50% males, 50% females). This is because statistical significance depends not only on the proportions found, but on the size of the sample. The sample sizes for children less than 75 cm were very small. c. Distribution of heights in the sample.

Height distributions for the total sample for cycles 1-3 and 4-6 are shown in Figure 5.1. There was a significantly higher percentage of children in the height category 55.1-65.0 cm in cycles 4-6 than in cycles 1-3. There was a significantly lower percentage of children in the height category 95.1-105.0 cm in cycles 4-6 than in cycles 1-3. No significant differences were found between the percentage of males and females in each height category in either cycles 1-3 or 4-6.


Figure 5.1. Height distributions m the total sample, cycles 1-3 and cycles 4

3. The nutritional status of children, total province.

Unless otherwise specified, results refer to children 75.1-115 cm in height. a. Means and distribution of percent weight for height, total province.

The percentage of children in each percent weight for height class for cycles 1-3 and 4-6 are shown in Figure 5.2. For both cycles 1-3 and 4-6 the largest percent of the sample fell between 80 and 89.9% weight for height. Males and females are aggregated because no significant differences were found between the percentage of males and females in each percent weight for height class in either cycles 1-3 or 4-6. In cycles 46, however, females had a higher mean percent weight for height than males (see Table 5.10).

Table 5.10 Mean percent weight for height and standard deviation by sex, Red Sea Province, cycles 1-3 and 46.

CYCLE

 

MALE

FEMALE

TOTAL

1-3

MEAN

86.68

87.04

87.26

 

SD

7.99

8.12

8.05

4-6

MEAN

88.08*

88.58*

88.34**

 

SD

7.76

8.05

7.90

* Significant difference between males and females (p<0.05).

** Significant difference between cycles 1-3 and 4-6 (p<.051.

For both cycles 1-3 and 4-6 the mean percent weight for height for the total sample was above 85% weight for height. The centre of the distribution therefore fell towards the upper limits of the 80-89.9% class.


Figure 5.2 Distribution of percent weight for height children 75.1-115 cm, Red Sea Province.

There was an upward shift in the distribution of percent weight for height between cycles 1-3 and 4-6. This is reflected in the mean percent weight for height which was significantly higher in cycles 4-6 than 1-3 (p<.05). There was a significant decrease in the percentage of the sample in the 80-89.9% weight for height class between cycles 1-3 and 4-6, and a corresponding increase in the 90-99.9% weight for height class over the same periods. Although there was a decrease in the percentage of the sample in the 70-79.9% weight for height class between cycles 1-3 and 4-6, this was not statistically significant. When all weight for height classes less than 80% weight for height were aggregated, however, the changes between cycles 1-3 and 4-6 became significant (see the Results section).

b. Rates of malnutrition, total province.

Children between 70% and 79.9% of their reference median weight for height are classified as "moderately malnourished". Children less than 70% of their reference median weight for height are classified as "severely malnourished". For the purpose of this report the following definitions have been used:

Malnourished - those children less than 80% of their reference median weight for height. This includes both moderately and severely malnourished children.

Severely malnourished - those children less than 70% of their reference median weight for height.

i. Percentage of malnourished children, total province.

The percentage of the total sample who were malnourished together with the 95% confidence interval for the population estimate, is shown in Table 5.11. Province-wide, there was no significant difference between the percentage of males and females who were malnourished. A significantly lower percentage of children were malnourished in cycles 4-6 than in cycles 1-3.

Table 5.11. Percent less than 80% reference median weight for height (malaourished) by sex, with 95% confidence intervals, Red Sea Province.

CYCLE

MALES

 

FEMALES

 

TOTAL

 
 

%

95% CI

%

95% CI

%

95% CI

1-3

16.68

1.36

16.65

1.43

16.63

0.49*

4-6

13.72

1.32*

12.64

1.35*

13.19

0.47*

* Significant difference in cycles 1-3 and 4-6.

ii. Percentage of severely malnourished children, total province.

The percentage of the total sample who were severely malnourished, together with the 95% confidence interval for the population estimate, is shown in Table 5.12.

Table 5.12 Percent less than 70% reference median weight for height (severely malnourished) by sex, with 95% confidence Intervals, Red Sea Province.

   

SEX

       

CYCLE

MALES

 

FEMALES

 

TOTAL

 
 

%

95% CI

%

95% CI

%

95% CI

1-3

1.89

0.43*

2.74

0.63*

2.27

0.43

4-6

1.36

0.44

1.34

0.47

1.35

0.32**

* Significant difference between males and females (p<.05).

** Significant difference between cycles 1-3 and 4-6 (p<.05).

In cycles 1-3 there was a significantly higher percentage of severely malnourished females than males. There was no significant difference in the percentage of severely malnourished males and females in cycles 4-6. The percentage of severely malnourished females decreased significantly between cycles 1-3 and 4-6, whereas the percentage of severely malnourished males stayed the same.

c. Malnutrition rates by district.

i. Percentage of malnourished children by district.

The percentage of the sample who were malnourished by district and sex, together with the 95% confidence interval for the population estimate, is shown in Table 5.13. There was a significant difference between the percentage of malnourished males and females in South Tokar District in cycles 1-3. A significantly higher percentage of males than females were malnourished. There were no other significant differences between the percentages of malnourished males and females by district, either in cycles 1-3 or 4-6.

Table 5.13. Percent less than 80% reference median weight for height (malnourished) by district and sex, with 95% confidence Intervals for the estimate.

   

CYCLES 1-3

CYCLES 4-6

DISTRICT

 

MALES

FEMALES

TOTAL

MALES

FEMALES

TOTAL

DERUDEB

MEAN

21.57

21.11

21.36

15.04

18.75

16.64**

 

CI

4.07

4.42

3.00

3.88

4.89

3.05

HALAIB

MEAN

14.90

15.13

15.02

8.25

6.51

7.38**

 

CI

3.58

3.49

2.50

3.23

2.89

2.19

HAYA

MEAN

20.30

19.10

19.76

18.12

15.99

17.11

 

CI

4.12

4.17

2.93

3.79

3.79

2.69

N.TOKAR

MEAN

11.50

14.15

12.73

11.65

11.40

11.53

 

CI

2.89

3.39

2.21

3.33

3.44

2.40

R.P.S

MEAN

10.75

11.70

11.15

10.45

9.46

10.00

 

CI

2.87

3.48

2.22

2.98

3.13

2.16

SINKAT

MEAN

18.18

20.94

19.46

14.35

10.45

12.41**

 

CI

3.86

4.16

2.76

3.43

3.05

2.30

S.TOKAR

MEAN

28.28*

20.00*

24.16

14.25

12.56

13.46**

 

CI

4.32

3.86

2.91

3.27

3.29

2.33

PROVINCE MEAN

16.68

16.65

16.63

13.72

12.64

13.19**

 
 

CI

1.36

1.43

0.49

1.32

1.35

0.47

* Significant difference between males and females.

** Significant difference between cycles 1-3 and 4-6.

From Table 5.13 the districts in Red Sea Province can be divided into two groups: those that showed a significant decrease in the percentage of malnourished children between cycles 1-3 and cycles 4-6, and those that showed no significant difference in percentage of malnourished children between cycles 1-3 and 4-6. Derudeb, Halaib, Sinkat and South Tokar Districts all had a significant decrease in the percentage of malnourished children between cycles 1-3 and 4-6. Haya, North Tokar and Rural Port Sudan Districts showed no change in the percentage of malnourished children between cycles 1-3 and 4-6. This is summarized in Map 5.1.

Map 5.2 shows a comparison of the percentage of the sample who were malnourished in each district for cycles 1-3 in relation to the province-wide mean percentage of malnourished children for cycles 1-3. Districts are ranked as above the province-wide mean, equal to the province wide mean, or below the province-wide mean with respect to the percentage of malnourished children. Map 5.3 shows the same information for cycles 4-6.


Map 5.1. Changes in malnutrition rates by district. cycles 1-3 to 46.


Map 5.2. Percentage of malnourished children, district means compared to province-wide mean. cycles 1-3.


Map 5.3. Percentage of malnourished children, district means compared to provincewide mean. cycles 46.

It should be remembered that the province-wide percentage of malnourished children was lower in cycles 4-6 than in cycles 1-3, and that the relation of each district to the province-wide mean should be interpreted in conjunction with the absolute district figures shown in Table 5.13. A district by district summary combining these data is given below.

DERUDEB: The percentage of malnourished children was higher than the provincewide average in cycles 1-3, and although it decreased significantly, still remained worse than average in cycles 4-6.

HALAIB: The percentage of malnourished children was equal to the province-wide average in cycles 1-3 and decreased significantly, resulting in a lower than average percentage of malnourished children in cycles 4-6. Halaib District was the only district with average or higher than average percentage of malnourished children to improve significantly between cycles 1-3 and 4-6.

MAYA: The percentage of malnourished children was higher than the province-wide average in cycles 1-3 and did not change significantly in cycles 4-6. Because the province-wide average percentage of malnourished children decreased between cycles 1-3 and 4-6 while the district average for Haya remained the same, the percentage of malnourished children in Haya was worse in relation to the rest of Red Sea Province in cycles 4-6 than in cycles 1-3. Haya district was the only district with a higher than average percentage of malnourished children that failed to improve between cycles 1-3 and 4-6.

NORTH TOKAR: The percentage of malnourished children was better than average in cycles 1-3 and did not change significantly in cycles 4-6. However because the provincewide average percentage of malnourished children decreased in cycles 4-6, North Tokar moved from being better than the province-wide mean in cycles 1-3 to being equal to the province-wide mean in cycles 4-6.

RURAL PORT SUDAN: The percentage of malnourished children was lower than average in cycles 1-3. The percentage of malnourished children did not change significantly between cycles 1-3 and 4-6, but despite the fact the province-wide mean improved, Rural Port Sudan still had a lower than average percentage of malnourished children in cycles 4-6.

SINKAT: The percentage of malnourished children was higher than average in cycles 1-3 but decreased significantly and were equal to the average in cycles 4-6.

SOUTH TOKAR: The percentage of malnourished children was higher than average in cycles 1-3 but decreased significantly and were equal to the average in cycles 46. The percentage of malnourished males decreased more than the percentage of malnourished females, so the significantly higher percentage of malnourished males than malnourished females found in cycles 1-3 was not found in cycles 4-6.

ii. Percentage of severely malnourished children by district.

The percentage of the sample who were severely malnourished broken down by district and sex, together with the 95% confidence interval for the estimate, is shown in Table 5.14.

Table 5.14. Percent less than 70% weight for height by district and sex, with 95% confidence Intervals for the estimate.

CYCLES 1-3 CYCLES 4-6

DISTRICT

 

MALES

FEMALES

TOTAL

MALES

FEMALES

TOTALS

DERUDEB

MEAN

2.21

4.40

3.20

0.88

2.34

1.51**

 

CI

1.46

2.20

1.29

1.01

1.89

1.00

HALAIB

MEAN

1.77

2.13

1.95

1.03

0.34

0.69**

 

CI

1.36

1.40

0.97

1.18

0.67

0.69

HAYA

MEAN

2.87

3.09

2.98

1.93

1.63

1.79

 

CI

1.71

1.83

1.25

1.35

1.32

0.95

N.TOKAR

MEAN

1.44

1.65

1.54

0.54

0.88

0.70

 

CI

1.08

1.24

0.82

0.76

1.01

0.63

R.P.S

MEAN

0.65

1.75

1.12

1.43

1.43

1.43

 

CI

0.75

1.42

0.74

1.16

1.27

0.86

SINKAT

MEAN

1.18*

3.93*

2.43

1.44*

0.50*

0.97**

 

CI

1.03

1.99

1.07

1.17

0.70

0.68

S.TOKAR

MEAN

4.37

3.95

4.16

1.32

1.23

1.28**

 

CI

1.96

1.88

1.36

1.07

1.09

0.77

PROVINCE MEAN

1.89*

2.74*

2.27

1.36

1.34

1.35**

 
 

CI

0.43

0.63

0.43

0.44

0.47

0.32

* Significant difference between males and females.

** Significant difference between cycles 1-3 and 4-6.

As noted previously, there was a significantly higher percentage of severely malnourished females than severely malnourished males in cycles 1-3. At the district level the significantly higher percentage of severely malnourished females than severely malnourished males was found only in Sinkat district, although many other districts showed a similar pattern but did not reach statistical significance, possibly because of small sample size.

No district had a percentage of severely malnourished children which was significantly different from the province-wide mean. Small sample size may have influenced the lack of statistical significance. The tendency was, however, for those districts with the highest rates of moderate malnutrition to have the highest rates of severe malnutrition.

4. Further characterisation of malnutrition in Red Sea Province.

a. Percentage of malnourished children by height category.

The total sample of children of all heights was broken down into height categories. The percent of children in each height category who were malnourished is shown in Figure 5.3. Children less than 55 cm were excluded because of extremely small numbers. No significant differences were found between the percentage of malnourished males or the percentage of malnourished females in any height category in either cycles 1-3 or 4-6.


Figure 5.3. Percent less than 80% reference median weight for height by height category, cycles 1-3 and 46.

In both cycles 1-3 and 4-6 the highest rates of malnutrition were seen in the height category 65.1-75 cm. High rates of malnutrition were also seen in children 55.165 cm. These results must be interpreted with extreme caution, however, because of the measurement technique used for the majority of children in these height categories. In children aver 75 cm tall highest rates of malnutrition were seen in the category 75.185 cm. Malnutrition rates then declined with height, and the lowest rates were seen in the tallest height category. There was a significant in the percentage of malnourished children in all height categories between cycles 1-3 and 4-6. The largest decreases were seen in the height categories 55.1 to 65 cm and 65.1 to 75 cm.

b. Percentage of malnourished children by season.

The results presented above are annual averages. It is important to understand the seasonal variations in malnutrition rates, for example to identify times of high risk, and to construct a framework with which to interpret the results of future surveys carried out at specific times of the year.

As described in the methods section, a season (major wet, minor wet, dry and harvest) was assigned to each case based on ecozone and time of year. Results from this analysis failed to detect seasonal differences; there were no significant differences between the mean percent reference median weight for height or the percentage of malnourished children between any of the seasons. This did not reflect the experience in the field, where May and June were described as the worst months for children's health, and January the best month, irrespective of ecozone. A further analysis was carried out by cycle, which corresponded to months of the year (see Table 5.3).


Figure 5.4. Percent less than 80% reference median weight for height by cycle. children 75.1-115 cm. Red Sea Province.

For the total province, the percentage of malnourished children peaked in September, then decreased in January and remained at this level until peaking again in September (Figure 6.4). Malnutrition rates were therefore worst in September, but improved by January to a level which is sustained for the rest of the year.

When broken down by district and cycle, two patterns emerge: Figure 5.5 shows the percentage of malnourished children by cycle for Halaib and Rural Port Sudan districts, and Figure 5.6 shows the percentage of malnourished children by cycle for the remaining districts of Derudeb, Haya, North Tokar, Sinkat and South Tokar. The latter group of districts followed the pattern described for the province as a whole. In Halaib district there was a steady decrease in the percentage of malnourished children with no seasonal variation apparent. In Rural Port Sudan there was some variation in the percentage of malnourished children, but it was small and not consistent with seasonality.


Figure 5.5. Percent less than 80% reference median weight for height (malnourished) by cycle, Halaib and Rural Port Sudan districts.


Figure 5.6. Percent less than 80% reference median weight for height (malnourished) by cycle, Derudeb, Haya, North Tokar, Sinkat and South Tokar Districts.

c. Percentage of malnourished children by settlement type.

The settlements visited by the Oxfam Port Sudan nutrition surveillance teams in cycles 16 were classified as being railway towns, towns, rural settlements or camps (settlements of displaced people that grew up during the drought). Table 5.15 gives the percentage of malnourished children by settlement type for cycles 1-3 and 4-6.

Table 5.15. Percentage of children less than 80% reference median weight for height (malnourished) by settlement type, cycles 1-3 and 4-6, with 95% confidence Intervals for the population estimate.

CYCLE

SETTLEMENT

CYCLES 1-3

CYCLES 4-6

 

MEAN

95% CI

MEAN

95% CI

RAILWAY

17.1

4.24

14.0

3.32

TOWN

19.5

2.66

10.6

2.17

RURAL

16.2

1.16

13.0

1.13

CAMP

24.5

4.14*

13.8

3.86

* Significantly different from other settlement types (p<.05).

There was a significantly higher percentage of malnourished children in the camps in cycles 1-3 than in all other types of settlements in cycles 1-3. There was no significant difference in the percentage of malnourished children in railway towns, towns and rural areas in cycles 1-3. There was no difference between the percentage of malnourished children in any of the settlement types in cycles 4-6.

d. Percentage of malnourished children by food security zone.

Red Sea Province was classified into three zones of drought impacts and food security for the years 1987 and 1988. Nutritional surveillance data for 1987 (cycles 4-6) were analyzed by "food security zone" for the same year. The percentage of malnourished children by food insecurity zone in cycles 4-6 are shown in Table 5.16.

Table 5.16. Percentage of children less then 80% reference rnedian weight for height by food security zone, cycles 4-6, with 95% confidence intervals for the population estimate.

FOOD SECURITY ZONE

N

MEAN

95% CI

HIGH SECURITY

1891

11.37

1.46

MEDIUM SECURITY

1535

12.77

1.70

LOW SECURITY

1029

15.74

2.27*

* Significantly different from other food security zones (p<.05).

There was no significant difference between the percentage of malnourished children in the high and medium food security zones. The percentage of malnourished children in the low food security zone was significantly higher than the percentage of malnourished children in the high and medium food security zones.

e. Percentage of malnourished children and the World Food Programme relief grain ration.

Mean percent reference median weight for height of children 75.1-115 cm for each settlement was correlated with the settlement average World Food Programme grain ration per family per day at the time of the nutritional surveillance. Spearman's rank correlation of mean percent weight for height with mean grain relief grain ration gave a correlation coefficient of -0.157 for cycles 1-3 and 0.008 for cycles 4-6. These correlation coefficients were not significantly different from zero. There was no correlation between mean percent weight for height and relief grain ration; the ration neither increased or decreased in a consistent pattern as malnutrition rates increased.

f. Variation In percentage of malnourished children within and between settlements.

One-way analysis of variance (ANOVA) of percent weight for height and settlement for cycles 1-6 showed that 12.9% of the total variation in percent weight for height could be explained by the relationship of percent weight for height to settlement. Unfortunately, Oxfam Port Sudan did not have the facilities to be able to carry out multiple regression on the nutritional surveillance data, so it was not possible to determine the amount of variance in percent weight for height explained by all the variables examined or their inter-relationships.

g. Comparison of Oxfam nutritional surveillance results with Sudan Emergency and Recovery Surveillance System (SERISS) results.

The Republic of Sudan Ministry of Health and USAID conducted four rounds of nutritional surveillance of children under five years old in the six northern regions of Sudan between May 1986 and July 1987. Red Sea Province was included in the surveys. Figure 5.7 shows the comparison of weight for height z-scores for children under five years old collected by SERISS, and weight for height z-scores for children less than or equal to 115 cm in height collected by Oxfam Port Sudan.

SERISS found consistently higher weight for height z-scores than Oxfam Port Sudan; children surveyed by SERISS had a better nutritional status than children surveyed by Oxfam Port Sudan. In the SERISS surveys, however, standard deviations of weight for height z-scores were as high as 2.73, whereas standard deviations for weight for height z-scores in the Oxfam surveys were close to 1.0. A similar seasonal pattern of changes in weight for height z-scores was seen in both surveys. Other SERISS findings which were similar to those of Oxfam Port Sudan included:

1. Nutritional status improved from 1986 to 1987.

2. High malnutrition rates were seen in the 12-21 month age group.

3. The smallest unit of analysis (the village council) was the single most important variable determining nutritional status.


Figure 5.7. Mean weight for height z-scores from SERISS and Oxfam nutritional surveillance, Red Sea Province

 

Conclusions

Unless otherwise specified, conclusions refer to children 75.1-115 cm in height.

1. Gender

a. There was a significantly higher percentage of males than females 75.1115 cm tall in Red Sea Province for both cycles 1-3 and 4-6. There was no significant difference in the proportions of males and females 75 cm or less for cycles 1-3 or 4-6.

b. There was no significant difference between the percentage of males and the percentage of females in each height category over 75 cm either in cycles 1-3 or 4-6.

c. There was no significant difference between the percentage of males and the percentage of females in each percent weight for height class in either cycles 1-3 or 4-6.

d. The mean percent reference median weight for height of females was significantly higher than the mean percent reference median weight for height of males in cycles 4-6, but the difference was so small as to be of little practical significance.

e. There was no significant difference between the percentage of malnourished males and the percentage of malnourished females in either cycles 1-3 or 4-6.

f. There was a significantly higher percentage of severely malnourished females than severely malnourished males in cycles 1-3. In cycle 46 there was no significant difference between the percentage of severely malnourished males and the percentage of severely malnourished females. The percentage of severely malnourished females decreased significantly between cycles 1-3 and 4-6, whereas there was no significant change in the percentage of severely malnourished males between cycles 1-3 and 4-6.

2. Province-wide results.

a. The height distribution of children in Red Sea Province changed between cycles 1-3 and 4-6. There was a significantly higher percentage of children under 75 cm in cycles 4-6 than in cycles 1-3, and a significantly lower percentage of children 95.1-105 cm in cycles 4-6 than in cycles 1-3.

b. For both cycles 1-3 and 4-6, the largest percentage of the sample fell into the 80-89.9% weight for height category, with the centre of the distribution towards the upper end of the class.

c. Mean percent reference median weight for height increased significantly between cycles 1-3 and 4-6, while both the percentage of malnourished children and the percentage of severely malnourished children decreased significantly between cycles 1-3 and 4-6.

3. District level results.

a. In cycles 1-3 Derudeb, Haya, Sinkat and South Tokar districts had a percentage of malnourished children above the mean for the province. Halaib district had a percentage of malnourished children equal to the mean for the province, while North Tokar and Rural Port Sudan districts had a percentage of malnourished children below the province mean.

b. Derudeb, Halaib, Sinkat and South Tokar districts all had a significant decrease in the percentage of malnourished children between cycles 1-3 and 4-6. In Haya, North Tokar and Rural Port Sudan districts there was no significant difference between the percentage of malnourished children in cycles 1-3 and cycles 4-6.

c. Of those districts with a higher than average percentage of malnourished children in cycles 1-3, only Haya district failed to improve in cycle 4-6. Of those districts with a percentage of malnourished children equal or lower than the average, only Halaib district improved in cycle 4-6.

d. In cycles 4-6 Derudeb and Haya districts had a percentage of malnourished children above the mean for the province. North Tokar, Sinkat and South Tokar districts had a percentage of malnourished children equal to the mean for the province, while Halaib and Rural Port Sudan had a percentage of malnourished children below the province mean.

4. Percentage of malnourished children by height category.

a. Highest rates of malnutrition were seen in the 65.1-75 cm height category in both cycles 1-3 and 4-6.

b. High malnutrition rates were found in children 55.1-65 cm.

c. For children over 75 cm tall, highest rates of malnutrition were seen in the 75.1-85 cm height category.

5. Percentage of malnourished chlidren and seasonality.

a. For the whole of Red Sea Province, the lowest percentage of malnourished children were found in January - April. Highest percentages of malnourished children were found in August and September.

b. When broken down by district, Halaib and Rural Port Sudan districts did not show seasonal fluctuations in the percentage of malnourished children.

6. Percentage of malnourished children by settlement types.

a. There was no significant difference in the percentage of malnourished children in railway towns, towns and rural areas.

b. In cycles 1-3 there was a significantly higher percentage of malnourished children in settlements classed as camps than in all other settlement types. In cycles 4-6 there was no significant difference between the percentage of malnourished children in railway towns, towns, rural areas or camps.

7. Nutritional status and the relief grain ration.

a. There was no correlation between settlement means for percent reference median weight for height and average World Food Programme relief grain ration per family per day.

8. Variation in nutritional status by settlement.

a. The smallest unit of analysis (the settlement) explained 12.9% of the total variance in percent weight for height for cycles 1-6.

9. Comparison of Oxfam nutritional surveillance results with SERISS results.

a. SERISS found consistently better nutritional status but greater variability in nutritional status in Red Sea Province than Oxfam nutritional surveillance teams.

b. SERISS and Oxfam nutritional surveillance had similar findings with respect to the improvement in nutritional status between 1986 and 1987: high risk of malnutrition in weaning age children, and the importance of the village in explaining variation in nutritional status.

 

Discussion

1. Gender differences in nutritional status.

From the figures for mean percentage reference median weight for height it would appear that females had a better nutritional status than males in Red Sea Province, although the difference was so small as to be of little practical significance. Equal proportions of males and females were malnourished, but in 1986 significantly more females than males were severely malnourished. In large samples relatively small but significant differences in mean percent reference median weight for height may be a reflection of differences in distributions above 80% weight for height. The mean percentage weight for height in two samples can be significantly different while the percentage of classified as malnourished is not, because of varying proportions in the different categories of well nourished children. Changes in mean percent weight for height can be used as an indicator of a worsening nutritional status in the community before increased malnutrition is seen. Mean percent weight for height also helps to describe the total distribution of percent weight for height in the sample. It is not safe to assume, however, that because one group has a higher mean percent weight for height than another (in this case females versus males), that the higher group has lower rates of malnutrition. From the results of this study, it would appear that females are at higher risk of malnutrition, particularly severe malnutrition, than males.

Significantly higher proportions of males than females were found in the samples from both cycles 1-3 and 4-6. We lack enough information to say whether these significant differences in proportions of males and females are a true reflection of a difference in the population, or are a result of a bias in the sample. If these figures are representative of the population, and assuming that the proportions of males and females are equal at birth, higher proportions of males than females in children 75.1-115 cm suggests a higher mortality rate in females than in males. This would be consistent with higher rates of severe malnutrition in females than in males, but there are no mortality data available to support or refute this hypothesis. Mortality data are important in interpreting change in nutritional status. An apparent improvement in nutritional status may be due to mortality in severely malnourished children. In Red Sea Province it is difficult to collect reliable mortality data as death, particularly in children, is a taboo subject. The health care infrastructure in the province is weak and the health information system extremely incomplete.

An alternative explanation of the unequal proportions of males and females is that the sample was not representative; that it was biased towards sampling males. There are no data on refusal rates by sex to arrive at this conclusion, but there remains the possibility that cultural factors may prevent women from bringing forward female children for measurement. One observation from the raw data: in some settlements the raw data is grouped into batches of males and females. This suggests that there may have been some division by gender during the process of assembling the children to be weighed. If this was the case, it would have added a complicating factor to the process of obtaining a truly random sample. If future surveys are undertaken, accurate records should be kept of refusals.

There is little information on infant and child feeding practices in Red Sea Province, and how they vary with the sex of the child. Colin Alfred undertook 10 weeks of field work in April - June 1986 in which he used open-ended questionnaires and interviews to collect information designed to increase understanding of the effect of food aid on communities. In discussion groups with women, a consensus emerged that "...boys ate more than girls, but not when they were young". The question of whether women felt that males needed more food than females was not addressed. Also, expressed opinions may not reflect practice, especially in times of stress.

2. Co-operation and "survey fatigue".

Although it is not within the scope of this report to comment extensively on survey design and practical difficulties in the field, there are some points that should be highlighted here. The percentage of places receiving repeat visits does reflect the possibility of different areas of a settlement being surveyed at each visit. In the case of larger settlements these areas could have been some distance from each other. Conversely, it is possible that in some areas one community leader would have to be consulted before a number of settlements could be visited. The number of repeat visits to individual community leaders could therefore be considerably higher than the number of repeat visits to individual settlements. The total number of visits by all Oxfam and non-Oxfam teams should be considered in assessing survey fatigue. Oxfam Food Monitors, World Food Programme Monitors, SERISS and Ministry of Health teams all toured Red Sea Province with varying frequency. The British Red Cross, Norwegian Red Cross, Euro-Action Acord, International League of the Red Cross and the Sudanese Red Crescent work in rural areas of Red Sea Province also.

The difficulties associated with survey co-operation increased not only with increasing numbers of visits, but with decreasing relief rations and decreased drought related stress. The unpopular and invasive nutritional surveillance was seen as a necessary evil associated with relief distribution. The nutritional surveillance teams themselves often emphasized the links between nutritional surveillance and the relief ration in an attempt to ensure co-operation. As discussed previously, refusal rates must be accurately recorded in the future. Refusal rates for an invasive and unpopular procedure are in themselves an indicator of stress in the community.

3. Changes in height distributions between cycles 1-3 and 4-6.

The increase in proportions of children less than 75 cm (approximately one year old) between cycles 1-3 and 4-6 was highly significant. Possible explanations for this change include:

a. Sampling bias.

b. An increased birth rate in cycles 4-6.

c. A decreased infant mortality rate in cycles 4-6.

Better maternal nutritional status would contribute to both an increased birth rate and decreased infant mortality. Again, the lack of vital statistics for the province and a lack of detailed data on refusal rates make it impossible to evaluate the change in the height distributions of the sample.

4. Nutritional status of children, total province.

Province-wide figures for mean percentage reference median weight for height and percentage of malnourished children provide a good starting point for describing nutritional status. The advantages of province-wide figures include a large sample size, which increases the probability of finding statistically significant results, and results that are not influenced by population shifts within the province (although Red Sea Province is far from a closed system, and population movement does occur across provincial boundaries). The disadvantage of province-wide results is that they mask variation within the province.

In Red Sea province as a whole mean percentage reference median weight for height increased, while the percentage of malnourished children decreased between cycles 1-3 and 46. The increase in mean percentage reference median weight for height was very small, and despite being statistically significant, is of little practical significance. The decrease in the percentage of malnourished children is encouraging, but we lack the historical data necessary to evaluate the degree of malnutrition in cycles 1-3 and 4-6 or the change between them in the context of what is usual variation in Red Sea Province.

There were no formal relief programme objectives in terms of nutritional status set at the beginning of the programme against which to assess the decrease in malnutrition.

Percentage reference median weight for height is a proxy indicator of nutritional status. The cut off of 80% weight for height for classifying malnutrition is largely arbitrary. We have no means of assessing what shifts in a proxy indicator around this arbitrary cut off really mean in terms of the health and welfare of children in Red Sea Province. More information is needed on the Beja perception of child health, acceptable and unacceptable levels of thinness and shortness in children of varying ages, and the expected variation in these both seasonally and in times of stress. By developing a locally appropriate cut off for malnutrition which could be used alongside international standards, future programme objectives could be both more realistic and aimed at a degree of change which has practical significance and visible impacts for the beneficiaries. Unless we have more detailed local information we are in danger of either devoting time and money to programmes which do not address a real need, or, more alarmingly, withdrawing from programmes when objectives which do not reflect needs have been met "successfully".

5. Variation in nutritional status by district.

With the exception of North Tokar, the nutritional status of children in the southern half of the province was worse than that of children in the northern half of the province. Although there is low rainfall in the north of the province, the absolute variability in rainfall is not great (see the accompanying paper by Roy Cole "Drought, food stress and the flood and rainfall record for Red Sea Province"). The north is therefore adapted to conditions of permanent drought, and did not experience a dramatic worsening of conditions in 1984/85. The worst nutritional status was seen in the south of the province, which has the highest variability in rainfall and flooding and experienced the biggest drought impacts in 1983/84. Nutritional vulnerability is not linked solely to absolute conditions but to variability in conditions and the degree and frequency with which exceptional conditions occur (see the accompanying paper by Roy Cole "Measuring drought and food insecurity in Red Sea Province in 1987 and 1988: a technique for the rapid assessment of large areas.").

The higher nutritional status of children in North Tokar district than the rest of southern Red Sea Province could be a reflection of the relatively rich resources of that district. These include agriculture in the Tokar delta and major khors, the economic opportunities and facilities associated with the town, and rich natural resources for local rural industry. South Tokar, which had the worst nutritional status in Red Sea Province in 1986, is exceptional also in that it has a high population of Beni 'Amer "refugees" who have become destitute through the combined effects of drought and restricted access to traditional grazing and agricultural areas in Eritrea caused by war. In addition, there is a high population of Eritrean refugees both in camps and absorbed into the areas around larger towns such as Garora. Traditional land rights restrict the movement of the Beni 'Amer into the North, the war in Eritrea has cut them off from their own traditional areas in the South, and the situation has been exacerbated by the pressure of incoming refugees. South Tokar district can be cut off from the rest of Red Sea Province for several months during late summer because of flooding in Khor Baraka.

Those districts with above average nutritional status in 1986 (North Tokar and Rural Port Sudan) did not improve in terms of percentage of malnourished children in 1987, despite a general improvement in nutritional status province-wide, regular relief food deliveries and good rainfall. Possible reasons for the lack of improvement include:

a. The level of malnutrition seen in these districts in 1986 represents the best possible level achievable in the prevailing conditions. That is, malnutrition is primarily a result of variables such as poor water supply, infectious disease, poverty and a lack of entitlement rather than a result of inadequate food supplies. This being the case, relief rations would not have a significant impact on malnutrition rates, and an alternative strategy focusing on primary health and a general strengthening of the ability to cope with environmental and economic variability would be more appropriate.

b. The level of malnutrition seen in these districts in 1986 is a level that is accepted either by individual families or the community. That is, the child's health and development are considered to be normal and there is no obvious functional disability, despite being below internationally recognised cut offs for malnutrition. This will be referred to as an "acceptable" level of malnutrition. Once this level is reached, resources may be thought to be more appropriately channelled into strategies to increase future security rather than into immediate household consumption. Given the extremely marginal and variable nature of the environment it is likely that long term strategies for increasing security would have a high priority once children were perceived as being out of danger. The comments made previously about the need to investigate local perceptions of malnutrition and their relation to child health and welfare apply here also. If a threshold of acceptable malnutrition does exist, and it is at a level which compromises child health and development, vulnerable children should be targeted with commodities specifically for their consumption rather than assuming that the benefits of a more general ration will trickle down. Examples such as corn soy mix (CSM) or a more varied basket of local commodities suitable for weaning foods are discussed above. Children are unlikely to benefit from supplementary foods when the food supply for the whole family is inadequate. A twopronged approach that ensures sufficient food for the family together with targeted foods for weaning age children stands the best chance of success.

Halaib district moved from having average rates of malnutrition in cycles 1-3 to having the lowest rates of malnutrition in Red Sea Province in cycles 4-6. Although the nutritional status of children in Halaib was better during cycles 1-3 than in several other districts, the changes seen in cycles 4-6 shows that there was still potential for improvement. Actual changes in nutritional status must be interpreted in terms of potential for change, which includes resource availability, prevailing conditions such as rainfall, and external inputs such as relief rations. The recent ERGO/Oxfam low level aerial survey of Red Sea Province has shown Halaib to be the least densely populated district, with an estimated population of approximately 17,000. This figure is substantially lower than the population estimate used for relief distribution. It is probable that the actual amount of relief grain distributed per family was considerably higher than that allocated. This, coupled with the fact that no severe drought effects were felt in Halaib district, may have contributed to the improvement in nutritional status.

Haya district was the only district with worse than average malnutrition rates that failed to improve between cycles 1-3 and 4-6. In cycles 4-6 Haya district had the worst malnutrition rate of any of the districts in Red Sea Province. The lack of improvement is particularly disturbing in view of the recent aerial survey findings that 28% of the total population of Red Sea Province lives in Haya district for all or part of the year. It was the district which suffered the worst drought impacts in 1983/84, and together with Derudeb the district in which camps for drought displaced people sprang up. There was no improvement in nutritional status between cycles 1-3 and 4-6 despite good rains and floods in Khor Arab, and regular relief distributions. Possible explanations for the lack of improvement must include those hypothesized for the lack of improvement in better than average areas; that the rate of malnutrition represents the best possible rate for the district, and/or the level was considered acceptable. The first explanation seems unlikely in view of the potential grazing, agricultural possibilities of Khor Arab and related areas, and the links and economic opportunities afforded by the railway and tarmac road.

Were relief rations allocated to Haya district inadequate? From the aerial survey figures it appears that the population of Haya district may have been underestimated, and the amount of relief actually available to each family less than that allocated Allocations and monitoring of relief in Haya district (with the exception of Tahamyam) was the responsibility of the Sudanese Red Crescent rather than Oxfam. The SRC has been and still is autonomous, and makes independent judgements on allocation levels. SRC seems to have been in favour of lower rations and more rapid ration reductions than was Oxfam policy for the rest of the province.

Another explanation for the continued poor nutritional status in Haya district could be that as families recovered from the effects of the drought they returned to their home areas, leaving behind a residual population of poor and destitute families. Alternatively, parts of families may have moved away leaving women, the elderly and sick children at the relief dumping points and camps. The populations being measured in cycles 1-3 and 4-6 would therefore not be comparable. With seasonal migration a strong feature of Beja life (and indeed an essential survival strategy) the problem of defining the population being surveyed at various times of the year applies to all districts and adds yet another complicating factor to survey design and the interpretation of results.

There is not enough information available to assess retrospectively the plausibility of any of the proposed explanations for the lack of improvement in nutritional status in Haya district. It is a pity that the emphasis of the nutritional surveillance was on a quantitative statement of the degree of malnutrition to the exclusion of a more holistic investigation of the causes of malnutrition. The quantitative approach was rooted in the original function of the nutritional surveillance teams for rapid assessment in an emergency situation, and failed to evolve with the changing emphasis of the relief programme and the changing conditions in the province. The opportunities to investigate and learn from situations such as the lack of change in Haya district were lost.

6. Malnutrition rates by height of the child.

The highest rates of malnutrition in Red Sea Province were found in children 65.1-75 cm in height. This corresponds to approximately ages 6-12 months. Disturbingly high rates of malnutrition were found in children 55.1-65 cm tall also. It would be expected that breastfeeding would play a major role in meeting nutritional requirements of children in these height categories, and therefore that rates of malnutrition would be relatively low. Aside from the possibility of a sampling bias towards babies who were sick, and the error introduced by the non-standard measurement technique used for children in these height categories, the high rate of malnutrition in under one year olds in Red Sea Province could be a reflection of inadequate breastfeeding and/or low birth weight babies who fail to catch up with expected growth patterns.

Reports from the field suggested that a large percentage of lactating mothers were unwell. Diseases such as scurvy and severe anaemia have been noted on field trips in 1988. Women do not have access to such a variety of foods as men because they are restricted to the tent. Men eat outside the tent, sharing food with neighbours. Men are served first, before women and children eat the remaining food. Men travel away from the community have the opportunity to eat in restaurants and coffee shops.

Maternal malnutrition affects both the quantity and quality of breast milk, particularly when the mothers' own body stores have been depleted by persistently poor nutritional intake and the stress of disease and pregnancy. Poor health could also affect infant feeding practices. Personal observations and anecdotal evidence from midwives suggest that some women who are in poor health will either stop breastfeeding or not establish breastfeeding even if their breast milk is adequate. Breast milk production is stimulated by feeding. If feeding stops or is infrequent a vicious cycle develops where breast milk production decreases and the mothers' perception of her inadequacy for breastfeeding is reinforced. More information is needed on women's perceptions of suitable and unsuitable health and environmental conditions for successful breastfeeding.

Maternal pre-pregnancy nutritional status and weight gain during pregnancy affect the birth weight of the infant. Poor nutritional status and low weight gain in pregnancy can result in low birth weight babies, who are effectively malnourished from birth and subsequently at high risk for diseases which would worsen their nutritional status further. A prerequisite for improving the nutritional status of children is to improve the nutritional status of women. All women of child bearing age should be considered for targeting as a vulnerable group. Particularly at risk are very young women who face the nutritional stresses of pregnancy and lactation before they have completed their own growth. In Red Sea Province it is common for women to be married and bearing children before they are out of their 'teens.

Targeting pregnant and lactating women for what the World Food Programme describes as "vulnerable group feeding" poses many problems besides the most obvious of identifying and reaching such women. Traditional practice is to restrict food intake in the third trimester of pregnancy to avoid large babies. Large babies are thought to cause difficult births, and to have been afflicted with the evil eye (belief in the evil eye is powerful and influences all aspects of rural Beja life). The period of food restriction coincides with the time that it is customary for a woman to leave her husband and return to her family for the birth; an extra mouth to feed in a household that may already be strained. In addition to a general restriction of food intake there are specific food taboos that apply in pregnancy. These seem to vary but examples of forbidden foods include eggs, dates and camel's milk. Any supplementary feeding programme must take such practices into account.

Policing household level food distribution is obviously impossible and undesirable. It is unlikely that commodities distributed for pregnant and lactating women will be consumed by them unless there is sufficient available for the whole family. One approach which has been used successfully in the Gambia is to provide pregnant and lactating women with high protein high energy biscuits which are less likely to be absorbed into the family food supply. This approach is impractical for Red Sea Province as there is no health care infrastructure through which to distribute the biscuits, large external inputs would be required, and the system would not be locally sustainable. Given adequate environmental conditions there is a sufficient quantity and variety of local foods to satisfy the nutritional requirements of pregnant and lactating women. What is needed is a greater understanding of women's support structures, their priorities for and control of their own income, their influence on decision making at various levels and how these change with factors such as wealth and drought related stress.

Of children over 75 cm tall, highest rates of malnutrition were found in the 75.185 cm height category. This corresponds approximately to children 12-24 months of age. In Red Sea Province weaning begins with the gradual introduction of supplementary foods between six and nine months of age, and is completed between 1824 months of age. Breast milk alone becomes inadequate to meet the nutritional needs of a child at around six months of age. Results from this study indicate that children of weaning age were at high risk of malnutrition. Children of weaning age have high energy and nutrient requirements for growth, but cannot take large quantities of food. Weaning foods must therefore have a high energy and nutrient density and be fed in small frequent amounts. In Red Sea Province weaning foods include ground sorghum porridge (asayda), goat milk, goat ghee, rice, and water in which dried dates have been soaked Sour milk and camel milk are not considered suitable for children. Breast feeding continues for up to two years, or until the woman becomes pregnant.

Successful weaning in rural areas is largely dependent on the availability of animal products such as milk, ghee and animal fat. The availability of these products varies both seasonally and from year to year. Replacements would be expensive and available only in towns. The vegetable oil and sugar provided in the relief ration are energy dense, but do not contain the wide range of nutrients found in milk and milk products. The vegetable oil (rape seed oil) is unpopular with some people because it has a fishy smell. It has been difficult to ensure equitable distributions of oil and sugar; they are valuable products which makes them particularly prone to "leakage". Oil and sugar may be sold by the recipients to provide cash. Sugar is highly prized and would be given preferentially to men and guests.

The most satisfactory way of permanently improving the health and welfare of weaning age children would be through long-term strategies to increase the resource base for pastoralism, investment in agricultural infrastructure and increased economic opportunities for the community as a whole. In the meantime, if a relief approach is adopted vulnerable weaning age children need to be targeted with more appropriate foods. Dried full fat vitamin A fortified milk is one, albeit controversial, possibility for the summer months when milk is in short supply. Corn soy mix was briefly distributed in Red Sea Province, with mixed reactions. Oxfam teams reported that the CSM was unpopular, and that women winnowed the mixture to extract the sugar. The Sudanese Red Crescent, however, reported enthusiastically that CSM had "the magical power to remove marasmus from our children" and asked for distribution to be extended. An alternative would be a relief ration that consisted of a more varied basket of nutritionally dense foods which would be suitable as weaning foods. Oxfam has tried this approach in some areas of Darfur, where families with malnourished children were targeted with a ration that included lentils and oil. An essential part of any such targeted programme would be an effective distribution and monitoring system. This should be done by women and through women, despite the difficulties that this poses in Red Sea Province.

Ideally, nutritional support to weaning age children would be part of a wider health care strategy that addresses issues such as immunisation and treatment of diarrhoea which directly affect nutritional status. Some common traditional medical treatments administered to children of weaning age result in either increased nutritional requirements because of physiological stress or decreased intake of nutrients. Examples include burning the head or other areas of the body to treat oedema (a common treatment for many other diseases also), and incising the gums and removing four teeth to treat tasniin. a disease associated with teething. Health and nutrition education for rural women should be increased. What primary health care facilities that are available concentrate on therapeutic rather than preventive and promotive health care. Community health workers are exclusively male.

7. Seasonallty In malnutrition rates.

Classification of seasons by month and ecozone failed to detect changes in malnutrition rate by season. The method used for classification was too rigid and insensitive to the great inter and intra-annual variation in rainfall and flooding seen in Red Sea Province. Seasonal changes in malnutrition rates are lagged behind the actual seasons. Changes are therefore masked, particularly as the rainy season is very short and the dry season long.

When re-examined by cycle, monthly changes in malnutrition rate became apparent. The worst rates of malnutrition were seen at the end of the dry season; the cumulative effect of the associated scarcity in cereals and grazing, reduced milk production and poor water supplies. Red Sea Province in the dry season is extremely harsh, with high temperatures and frequent dust storms. The incidence of respiratory and eye infections increases dramatically in the summer months, part of a vicious cycle of worsening nutritional status and increasing disease susceptibility. Lowest rates of malnutrition were seen in January and February, after the rainy season and harvest, and when improved grazing has resulted in increased milk production and livestock numbers.

When broken down by district the pattern of seasonal changes in malnutrition rates was not seen in the north of the province (Halaib and Rural Port Sudan districts). As discussed previously, the north of the province receives very little rainfall, and the distinction between the seasons is blurred. Seasonal changes in malnutrition rates in Rural Port Sudan district may have been modified by access to the supplies and facilities available in Port Sudan. Greatest seasonal variation in malnutrition rates occurred in the south of the province, which has the highest variability in rainfall and flooding.

It is essential to take seasonality into account when comparing results of nutritional surveys conducted at different times of the year. Otherwise, an improvement in nutritional status could be unjustifiably attributed to an intervention such as provision of relief radons when it is a reflection of normal intra-annual variation.

The provision of a stable relief ration throughout the year did not mask seasonality in malnutrition rates. This could be for three reasons:

a. The ration did not provide the total requirements for energy and nutrients.

b. In terms of nutritional value, sorghum, oil and sugar are not a substitute for milk and milk products which are essential for children and are always in seasonal short supply unless the family has a large herd and is highly mobile.

c. Non-food factors which influence malnutrition rates and vary seasonally, such as disease incidence, are playing an important role in the aetiology of malnutrition in Red Sea Province.

8. Malnutrition rates by settlement type.

Camps for drought displaced families sprang up in early 1985, largely in Haya and Derudeb districts. They were usually associated with an existing town. The nutritional status of children living in settlements classified as camps was significantly worse than the nutritional status of children living in other settlement types in 1986, but not in 1987. The improvement in the nutritional status of children in camps in 1987 could have been due to either or both of the following:

a. Camps being disbanded and families returning to their home areas, leaving a residual urbanised population and blurring the distinction between camps and towns.

b. The nutritional status of the camp inhabitants improved.

There was no difference between the nutritional status of children living in railway settlements, towns and rural areas. It was expected that the nutritional status of children in railway towns would be better than the nutritional status of children in towns or rural areas. Railway workers were relatively well paid in 1986 and 1987 (LS 350 per month), they have access to food supplies delivered by train, and water supplies are delivered by tanker from Atbara or Port Sudan. This was not the case. Possibilities for the lack of difference between railway towns and other settlements include:

a. Within railway towns the children of railway workers were not differentiated from the children of non-railway workers.

b. The majority of people living close to the station are not employed by the railway.

c. Railway towns have large satellite communities who have settled to take advantage of the facilities, often because of stress in their home areas. Railway towns could therefore be made up of two populations; relatively advantaged railway workers, and disadvantaged rural people on the periphery. This would not have been picked up from the previous survey design.

d. There could have been no difference in the nutritional status of wealthy and poor families, either because malnutrition was caused by non-food factors or because the level of malnutrition was one which was acceptable to wealthier families. Oxfam nutritional surveillance teams in Darfur found no difference in rates of malnutrition in the children of wealthy or poor families.

The possibilities outlined above apply to the lack of difference between the nutritional status of children in towns and rural areas also. Towns have more facilities and economic opportunities than rural areas, but also have a peripheral population of very poor families. It is possible that similar populations are being measured in towns and rural areas as families move between them at different times of the year.

9. Rates of malnutrition by food security zone.

As might be expected, areas with low food security and high drought impacts had higher rates of malnutrition than areas with medium and high food security and low drought impacts. There was no difference, however, in malnutrition rates between areas with medium and high food security and low drought impacts. Possible explanations for this include:

a. An acceptable rate of malnutrition is reached in the medium food security zone, and represents a threshold below which malnutrition rates do not improve despite increased food security.

b. Malnutrition in areas with medium or high food security is caused largely by factors not related to food availability.

c. The food security zones are too large and mask variability within them. The zones were based on ecological rather than human criteria. There was a general east-west bias in the zoning, whereas differences in nutritional status seem to vary more in a north-south direction. A more detailed analysis of food security in Red Sea Province has since been carried out, but because of time pressures could not be included in this analysis.

d. Migration between the food security zones could have resulted in the same populations being measured in different food zones at different tames of the year.

If points a and b are valid, the usefulness of nutritional status as an indicator of food security is reduced. If point d is valid, it needs to be a major consideration in planning future sampling strategies.

10. Malnutrition rates and the relief ration.

The calculation of the average relief grain ration per family for the cycle during which the nutritional surveillance took place was not ideal. Nutritional status is a lagged variable; it does not change immediately but reflects conditions at some time in the past. To fully understand the relationship between the relief ration and malnutrition rates a historical perspective is necessary. Changes in malnutrition rate should be examined in relation to relief input over time rather than looking for relationships between absolute figures at one point in time. Unfortunately neither the Relief Section records nor the nutritional surveillance data were in a form which could be used in a longitudinal analysis without considerable work, well outside the time frame for this study. Coordination between the Relief Sections and nutritional surveillance teams to collect data in a form that would be amenable to continuous longitudinal analysis should be a priority in planning future relief efforts. Examples include better co-ordination between relief allocation zones and sampling units for nutritional surveillance, consideration of the timing of relief distributions in planning the frequency and timing of nutritional surveillance, more serious efforts to time relief deliveries on a regular basis, and making available cumulative records of relief inputs and running averages for allocations.

The calculation of the average relief grain ration per family per day at the time of the nutritional surveillance was considered worthwhile despite the limitations outlined above. This was for three reasons:

a. It was the best measure of average relief rations available.

b. As a rule, relief allocations did not vary greatly within one dumping point in 1986 and 1987.

c. The beneficiaries are thought to manage deliveries in such a way as to smooth fluctuations in the availability of grain through the cycle. Examples include borrowing grain against the next relief delivery if that delivery is delayed.

The lack of correlation between malnutrition and the relief ration is probably best explained by the limitation of the analysis outlined above. Other factors which complicate a direct relationship between the relief ration and malnutrition rates include:

a. Food availability may not be reflected directly in malnutrition rates because of the influence of non-food factors in the aetiology of malnutrition, and because of the possibility of an acceptable level of malnutrition (as discussed previously).

b. The nutritional status of children may not necessarily reflect the total needs of an area for relief input. Improving the nutritional status of children was not the only goal of this relief operation, and the need for relief could therefore remain after malnutrition rates have reached their lowest possible rates.

c. Nutritional surveillance data were not, or possibly never could be, appropriate in terms of time and space to make a meaningful contribution to the cycle by cycle management of relief allocations. Could such data be used more appropriately for long term planning and evaluation (for instance setting annual targets for total inputs), and/or more detailed case study type information to address the causes of malnutrition, which in turn would guide policy?

11. Variation in malnutrition rates by settlement.

In the 1986/87 Sudan Emergency and Recovery Surveillance System (SERISS) study of nutritional status in Northern Sudan (Ministry of Health/USAID), 28% of the total variation in weight for height z-scores was explained by the 22 variables examined in the survey. The remaining 72% of variation remained unexplained The Oxfam nutritional surveillance teams collected information on similar but fewer variables than the SERISS survey, and it is unlikely that regression of the Oxfam data set would result in a higher percentage of explained variance in nutritional status than that found in the SERISS study. If the SERISS figure of 28% explained variance is taken as a guide, the effect of settlement in explaining variation in percent weight for height in the Oxfam survey was considerable. It is probable that settlement was the single most important variable in explaining variation in nutritional status in the Oxfam data set, as it was in the SERISS data set. The practical implications of this finding are:

a. Sampling should include as many settlements as is practical in order to ensure an accurate assessment of the district and province In Red Sea Province family size is small and the number of children present in each settlement typically small. Sampling therefore inevitably involves visiting a large number of individual settlements.

b. Investigations of the causes of malnutrition should concentrate on looking at individual settlements and the differences between individual settlements which are influencing nutritional status. This was the approach taken by the nutritional surveillance teams in 1988 and 1989 (see the paper by Fatma Gebreil "An analysis of areas in Red Sea Province with persistently poor nutritional status", Oxfam Port Sudan 1989.).

c. General relief rations and/or supplements for vulnerable groups need to be targeted by settlement. Within one allocation zone there will be a wide range of need. This implies close monitoring by people with detailed local knowledge.

The importance of the settlement in explaining variation in percentage weight for height is probably the result of it being the smallest unit of analysis in the study. Factors affecting even smaller units such as the individual tent or family group may prove even more important in explaining variation in percent weight for height than those which affect settlements, but in rural Red Sea Province at the present time research at the household level is difficult to the point of practical impossibility.

12. Comparison of Oxfam nutritional surveillance results with SERISS results.

The persistently higher nutritional status found in the SERISS surveys than in the Oxfam surveys is most likely to be a result of differences in the sampling frames, the sampling intensity and the distribution of the sampled areas in the two studies. It is not a case of one study being "right" and another "wrong", but rather of them providing different information for different uses. The Oxfam nutritional surveillance had Red Sea Province as the area of study, with the district as the unit of analysis. The SERISS study had Northern Sudan as the area of study, with the province as the unit of analysis. Oxfam sampled exclusively from rural areas, whereas SERISS stratified their sample by urban and rural population.

The urban component of the SERISS study was probably responsible for the higher nutritional status than was found by Oxfam. In addition, SERISS sampled in fewer districts and settlements than Oxfam. As has been discussed previously, this would have important implications for capturing all the variation in nutritional status found in Red Sea Province. It would be valuable for Oxfam to collect or collate more information on the nutritional status of children in Port Sudan. Seasonal migration of families to Port Sudan means that the urban populations in some strongly Beja areas of the city such as Daym al-'arab could be the same as the population being measured by Oxfam nutritional surveillance teams in rural areas. Periods spent living in Port Sudan could be an important factor influencing the nutritional status of such populations.

 

Future directions.

The tendency has been for Oxfam to use the nutritional status of children as an indicator of the wellbeing of the community and to provide general assistance with the hope that benefits will reach all sections within the community. Improving the nutritional status and hence the health and welfare of children in Red Sea Province should become 1) a practical programme goal with both long-term development initiatives and immediate targeted interventions, and 2) focused on gender issues. If Oxfam is not to do this directly, it should act as an advocate with government and other agencies to promote the interests of women and children.

Oxfam should take the initiative in developing innovative ways of assessing nutritional status in the field. The Oxfam philosophy of the bottom-up approach should not be restricted-to development. What is needed in Red Sea Province is a greater understanding of the Beja perceptions of normal and abnormal child health and development. Appropriate local cut offs could then be used alongside the international standards for measuring nutritional status which are currently accepted by donors. This would greatly enhance our ability to both plan programmes and evaluate changes in the field in a context which is appropriate for the local people. Methodological issues which have arisen as a result of Oxfam's experiences in Red Sea Province should be addressed promptly and incorporated into guidelines that could be used in the event of future relief efforts in Red Sea Province.

 

Appendix 5.1. Data collection form, nutritional surveillance teams, Oxfam


Data collection form, nutritional surveillance teams, Oxfam

 

Appendix 5.2. Claasifications of coded variables.

COLUMN

TITLE DESCRIPTION

   

A

NUM

Case number

 

B

DIST

District

1=Derudeb

     

2=Halaib

     

3=Haya

     

4=North Tokar

     

5=Rural Port Sudan

     

6=Sinkat

     

7=South Tokar

C

VILL

Village

 

D

C

Cycle

1-6

E

M

Month

1-12

F

Y

Year

Last two numbers

G

FZ

Food Security Zone

1=High security

     

2=Medium security

     

3=Low security

     

4=No data

H

S

Season

W=Wet

     

H=Harvest

     

D=Dry

I

EZ

Ecozone

1-25

J

T

Settlement type

1=Station

     

2=Town

     

3=Rural

     

4=Camp

K

HL

Measurement type

H=Height

     

L-Length

L

A

Age by report

0=Less than 1 year

     

1=1 year or over

M

H

Health

G=no illness

     

S=Illness recorded

     

K=Oedematous

N

S

Sex

M=Male

     

F=Female

O

HT

Height/Length (cm)

 

P

WT

Weight (kg)

 

Q

%PRW % weight for height, non sex-specific

   

R

%SEXRW % weight for height, sex specific ref.

   

S

Z

Z-score

 

 

Appendix 5.3. Ecozones in Red Sea Province (from Watson, 1976).


Ecozones in Red Sea Province (from Watson, 1976).

 

Appendix 5.4. Seasons by month and ecozone, Red Sea Province.

ECOZONE

   

SEASON

   
 

Major

Minor

Harvest

Best

Worst

 

Rain

Rain

Season

Health

Health

1

Oct-Jan

Jun-Sep

Jan-Mar

Jan

May-Jun

2

Oct-Dec

Jul-Sep

Dec-Jan

Jan

May-Jun

3

Oct-Dec

   

Nov-Jan

Jun-Sept

4

Jul-Dec

Jul-Sep

Jan-Feb

Oct-Dec

May-Jun

5

Oct-Dec

Jul-Sep

Dec-Jan

Jan

May-Jun

6

Jul-Aug

Oct-Dec

Sep-Oct

May-Jun

 

7

Jul-Sep

Nov-Dec

Sep-Oct

Oct

May-Jun

8

Jul-Sep

Oct-Dec

Sep-Nov

Oct-Jan

May-Jun

9

Jul-Sep

 

Sep-Nov

Oct

May-Jun

10

Jul-Sep

   

Dec-Jan

Sep-Oct

12

Jul-Sep

Oct-Dec

Sep-Nov

Oct

May-Jun

14

Jul-Sep

Oct-Dec

 

Sep-Oct

May-Jun

15

Jul-Sep

Oct-Dec

Oct-Jan

Oct-Jan

May-Jun

16

Jul-Sep

Oct-Dec

 

Sep-Oct

May-Jun

17

Oct-Dec

Jul-Aug

Dec

Jan

May-Jun

18

Jul-Sep

Oct-Dec

 

Sep-Oct

May-Jun

20

Oct-Dec

Jul-Sep

 

Jan

May-Jun

23

Jul-Sep

Oct-Dec

 

Sep-Oct

May-Jun

24

Jul-Sep

Oct-Dec

Sep-Nov

Oct

May-Jun

25

Jul-Sep

Oct-Dec

Sep-Nov

Oct-Jan

May-Jun

 

Appendix 5.5. Classification of fled Sea Province into food security zones, 1987.


Classification of fled Sea Province into food security zones, 1987.

 

Appendix 5.6. Locations of sampled sites, nutritional surveillance cycle 1.


Locations of sampled sites, Nutritional Surveillance Cycle 1.

 

Appendix 5.7. Names of sampled sites, nutritional surveillance cycle 1.

DERUDEB

Al-konet, Amberkiateb, Gasangayef, Larlik, Ormis, Shoshoiyeb, Tehilla.

HALAIB

Adaldayb, Al-jarif, Eit, Al-kuk, Fodikwan, Harawary, Kajakabab, Kamoreb, Sharem, Shashoisharab, Shashol, Todor, Tomandra, Tumeray.

HAYA

Alatit, Hamasit, Hormatal, Ibli, Nafti, Okliss, Togna.

NORTH TOKAR

Agwatiro, Aswit, Basugayt, Dolobiay, Enkiateb, Fada, Gabayab, Galalayma, Hamdayab, Keray Salambot, Lui, Mant, Mays, Sitereb, Toraft.

RUKAL PORT SUDAN

Adabay, Agariry, Baldangel, Hamli, Handuub Beja, Handuub Rashayda, Tugalhuush, Yudib.

SINKAT

Abent, Amayt, Enderkwan, Gebeit Ashraf, Hansut, Ikamab, Labba, Nasit, Olhud, Yawana.

SOUTH TOKAR

Adart, Adobana, Agatay, Agig, Aiterba Rural, Aiterba Town, Al-adliba, Andel, Garora Rashayda, Garora Rural, Garora Souk, Halfa, Ma'arafiit.

 

Appendix 5.8. Locations of sampled sites, nutritional surveillance cycle 2.


Locations of sampled sites, nutritional surveillance cycle 2.

 

Appendix 5.9. Names of sampled sites, nutritional surveillance cycle 2.

DERUDEB

Adarot, Ambirkiateb, Arift, Balak, Dirbab, Ganyota, Gasangayef, Hamboli, Matayt, Sugudeb, Tadamay, Tisibrihimit, Tolik.

HALAIB

Aydeb, Deruba, Efangwab, Fodikwan, Gebeit Alma'adiin, Hamiyamayb, Handukteb, Harankuk, Ogra, Sararashambi, Shalatayn, Sofaya, Soodi, Todor.

HAYA

Al-ganay, Amrin, Aryab, Awayt, Eikyab, Halag, Kokryeb Abadab, Kokryeb Magwalla, Oger, Ofin, Sanganeb, Siyeteb, Tiksasit, Timiki, Tolugreb.

NORTH TOKAR

Amayb, Ashat Rural, Dolobiay, Erim, Gabayab, Gabol, Hamdayb, Lui, Mays, Odwaan, Sitareb, Triktiay.

RURAL PORT SUDAN

Adabay, Adryab, Daruur, Handuub, Kalkowi, Li'it, Obo, Sallum, Salwadeb, Tobayn, Tomaala Almasjid, Tomaala Hayli.

SINKAT

Abent, Agwamt Hamlayt, Amigwolad, Biranfi, Dimyat, Erert, Gebeit Ashraf, Hansuut, Haritri, Hilayat, Nasit, Nobahaweb, Saguteb, Tabakly.

SOUTH TOKAR

Adobana, Agatay B. Aiterba Town, Al-adliba, Andel, Aydeb, Derhayb, Agig, Garora Town, Halfa, Ma'arafiit Rural, Ma'arafiit Town, Rikaab, Shabri.

 

Appendix 5.10. Locations of sampled sites. nutritional surveillance cycle 3.


Locations of sampled sites. nutritional surveillance cycle 3.

 

Appendix 5.11. Names of sampled sites, nutritional surveillance cycle 3.

DERUDEB

Adarot, Andrayef, Arift, Awagayt, Delay, Dirbab, Ganyota, Hamboli, Hamteb, Tadamay, Tamlayt.

HALAIB

Al-kuk, Al-shalal, Aydeb, Dait, Dungunab, Gabatit, Hadi, Handukteb, Lolignet, Sofaya, Sukanholt, Todor, Yumunt.

HAYA

Alanabib, Alatit, Alganay, Amrin, Asot, Gadayt Tangaday, Hormatal, Kamoyab, Kilanyeb, Ogrin, Siyeteb, Tiksasit, Tolugreb, Yahamyab.

NORTH TOKAR

Amayb, Ashat, Dolobiay, Fatit, Gabol, Islabib, Nowlabab, Odwaan, Sitareb, Triktiay, Warram.

RURAL PORT SUDAN

Adalgurbab, Al-baab, Darabshashowi, Daruur, Kalkowi, Kisibiyai, Obo, Sallum, Taiglin, Tobayn, Towai.

SINKAT

Adalaweb, Amigwolad, Dabarayt, Erkowit, Hagrab, Hansut, Khor Bolib, Nafilyament, Satim, Tabakly.

SOUTH TOKAR

Adart, Adobana, Agig, Aiterba, Al-adliba, Garora, Halfa, Ma'arafiit, Ma'arafiit Rural, Shabri.

 

Appendix 5.12 Locations of sampled sites, nutritional surveillance cycle 4.


Locations of sampled sites, nutritional surveillance cycle 4.

 

Appendix 5.13. Names of sampled sites, nutritional surveillance cycle 4.

DERUDEB

Abusalarna, Agwatay, Ambirkiateb, Balak, Gawtit, Kinabanayeb, Kodit, Sararatiyef, Sugudeb, Tamlayt, Tindera.

HALAIB

Aljarif, Arakiay, Delaw, 'Is, Eit, Fodikwan, Hadaya, Kelayet, Shashoi Gumadryab, Shenab, Soodi.

HAYA

Adalhuf, Al-rogel, Asot, Enha, Hamadayt, Hankalaweb, Kalhashtribab, Labba, Myas, Ofin, Sanganeb, Shortayn, Taharis, Togna.

NORTH TOKAR

Agwatay, Ashat Bilasiit, Aswit, Dahant, Enkiateb, Gabayab, Hamdayb, Mays, Odwaan South, Sitareb Bushbelt, Sitareb Rashayda.

RURAL PORT SUDAN

'Amuur Maluuf, Batra, Garamayt, Hadayt Guba, Kajaret, Komosana, Oshiri, Serkoyt, Shandoday, Tugalhuush Coast, Tugalhuush Mountain.

SINKAT

Airaweb, Amayt, Ashuf, Asot, Bramyo, Dabitaweb, Geneteb, Haritri, Labba, Nasit, Olhud, Onil, Shakan, Tomasay.

SOUTH TOKAR

Adart, Agatay A, Aiterba Clinic, Aydeb, Ayet, Derhayb, Garora, Gowi, Hambukeb, Mahmuud Salih Bush, Ma'arafiit Hasra, Sebat, Warhat.

 

Appendix 5.14 Locations of sampled sites, nutritional surveillance cycle 5.


Locations of sampled sites, nutritional surveillance cycle 5.

 

Appendix 5.15. Names of sampled sites, nutritional surveillance cycle 5.

DERUDEB

Adarot, Delay, Gadamay, Ganyota, Garada, Gasangayef, Sogodeb, Tolik.

HALAIB

Adaraweb, Aykwan, Aytery, Balwayitsha, Elkuk, Fodikwan, Gebeit Alma'adin, Kuratry, Lolignet, Sararashambi, Shashoisharab, Sofaya.

HAYA

Aldawir, Al-kilo, Amrin, Aryab, Hadaweb, Kasalwadi, Musmar Town, Shora, Siyeteb, Taham, Tiksasit, Timiki, Yahamyab.

NORTH TOKAR

Ashat, Ashat Souk, Dolobiay, Erim, Erwit, Gabayab, Gabol, Galalayma, Nowlabab, Sitareb, Tantiu.

RURAL PORT SUDAN

Abunaggara, Adafab, Adalaweb, Adryab, Daytry, Handuub, Ibrahimayt, Kadaweb, Kisibiyay, Odi, Salwadeb, Shalhat, Toksar.

SINKAT

Adalhuf, Amigwolad, Andraydyab, Arab, Biranfi, Erert, Hamashyameb, Harasab, Harmanab, Hashatribab, Makida, Manaweb, Nobahaweb, Oshger, Summut.

SOUTH TOKAR

Adobana, Agatay B. Agig, Aiterba, Aiterba Ablay, Aiterba Rashayda, Aladliba, Al-adliba Rashayda, Derhayb, Gelhent, Ma'arafiit, Shoshiay, Shoshiay Rural, Warhat.

 

Appendix 5.16. Locations of sampled sites, nutritional surveillance cycle 6.


Locations of sampled sites, nutritional surveillance cycle 6.

 

Appendix 5.17. Names of sampled sites, nutritional surveillance cycle 6.

DERUDEB

Ayob Khalwa, Gadamay Albar, Gahwat Algabab, Makekulay A, Manar Masjid, Matayt, Sugudeb.

HALAIB

Arakiay, Delaw, Dungunab, Eit, Gabatit, Hadaya, Khasham Gabatit, Shenab, Tomandra, Yumunt.

HAYA

Adalhuf, Balatribab, Ebarashit, Eikyab, Eraway, Hamadayt, Kass, Kokreyb Abadab, Myas, Shediyab, Tolugreb, Yomalal.

NORTH TOKAR

Agwatiru, Ashat Bilasiit, Dahant, Enkiateb, Fatit, Komideb, Mays, Odwaan, Odwaan South, Sitareb Bushbelt, Sitareb Rashayda.

RURAL PORT SUDAN

Agwamt Tosaara, Baldangel, Daruur, Gashiyt, Kalkowi, Lakateche, Sallum, Tugalhuush, Tomaala Almasjid, Tomli.

SINKAT

Alla Akbar, Amayt, Baharoty, Bilasiit, Bramyu, Dabarayt, Dabitaweb, Deokwan, Gebeit Ashraf, Halgit, Harmanab, Hilayat, Labba, Tehib, Telya.

SOUTH TOKAR

Adart A, Adart B. Aiterba Clinic, Aiterba Souk, Garora, Hasra, Hilayat Hasra, Mahmuud Salih Bush, Rikaab, Shabri, Traf Alhaysham, Warhat.

 

 

6. The nutritional status of children in Red Sea Province, July-October 1989: a supplement to the November 1985-November 1987 results. Mary L. Cole and Roy Cole

 

Summary

Nutritional surveillance teams at Oxfam Port Sudan undertook one provincewide survey of the nutritional status of randomly selected children less than equal to to cm in height in Red Sea Province between July and October 1989. The survey was undertaken in order to provide a representative overview of the nutritional status of children in Red Sea Province after the generally exceptional rains Of 1988, and as relief distributions in the province came to an end. The survey was designed to be directly comparable with those done by Oxfam in 1986 and 1987.

The percentage of children less than 8096 reference weight for height (malnourished) in Red Sea Province declined significantly between 1987 and 1989. The decrease was, however, restricted to females. There was no significant change in the percentage of malnourished males between 1987 and 1989. In 1989 there was a significantly higher percentage of malnourished males than malnourished females. The percentage of children less than 70% reference median weight for height did not change significantly between 1987 and 1989. In 1989 significantly more males than females were malnourished, a reversal of the situation in 1986.

At the district level, only Halaib district had a percentage of malnourished children which was significantly higher than that in 1987. South Tokar was the only district to have a percentage of malnourished children higher than the province-wide mean in 1989. The continued high rates of malnutrition in males in Haya district, together with the increased rates of malnutrition in males in Rural Port Sudan are causes for concern and highlight the importance of further research into gender differences in nutritional status.

Diarrhoea and vomiting were the most frequently reported illnesses in both malnourished and severely malnourished children. All severely malnourished children had a concurrent illness, but 40% of malnourished children had no identifiable disease at the time of the survey. More information is needed about the functional significance of the 80% weight for height cut off to the health and development of children in Red Sea Province.

Oxfam nutritional surveillance teams met with continued fierce resistance to the weighing and measuring of children. This not only biases sampling, but is in danger of jeopardising the type of relationship between Oxfam and the Beja which is vital for successful long term development initiatives. Alternative methods of nutritional surveillance should be investigated.

 

Introduction

During 1988 the nutritional surveillance teams at Oxfam Port Sudan changed their method of work, moving away from province-wide surveys towards a more detailed study of the causes of malnutrition at the settlement level (see "An analysis of areas with persistently poor nutritional status", Fatima Gebreil, Oxfam Port Sudan 1989). In 1989, however, it was decided to undertake one further province-wide survey of the nutritional status of randomly selected children less than or equal to 115 cm in height. This was in order to obtain statistics which would be both representative of the whole province, and directly comparable to those obtained in 1986 and 1987. Such an analysis was thought appropriate for two reasons:

1. To determine the nutritional status of children after the exceptional rains which fell in parts of Red Sea Province in 1988, and

2. To provide an overview of the nutritional status of children in Red Sea Province as relief distributions came to an end.

One province-wide tour of the seven districts in Red Sea Province was therefore undertaken between July and October 1989. It is to the credit of the teams involved that the work was completed successfully despite constant and varied interruptions, harsh summer weather, severe food shortages and the additional work created by the low level aerial survey of Red Sea Province.

 

Methods

The methods used for the six province-wide surveys of the nutritional status of children in Red Sea Province during 1986 and 1987 were duplicated in this study. These methods are described in detail in the previous paper (Cole, M. and Cole, R. (1989) The nutritional status of children in Red Sea Province, November 1985 November 1987). Minor changes to this method included the use of large note books to record data in the field rather than the form used in 198687 and the collection of more detailed information on the general condition of each child and his or her parents. Percent less than 80% reference median weight for height by settlement was calculated in the field rather than the office, which had previously been the case. On returning to the office, results were reanalysed by computer, using a spreadsheet and sex-specific reference tables (WHO/NCHS/CDC 1983). The sample was divided into those less than or equal to 75 cm in height and those greater than 75 cm in height as described in the previous paper.

 

Results

All results refer to children 75.1-115 cm in height unless otherwise specified.

1. Description of the sample.

Table 6.1. Sample size, nutritional surveillance Red See Province 1989.

 

<= 75 CM

 

> 75 CM

     
 

MALE

FEMALE

TOTAL

MALE

FEMALE

TOTAL

DERUDEB

22

33

55

100

93

193

HALAIB

21

22

43

103

97

200

HAYA

35

30

65

100

97

197

N.TOKAR

40

28

68

108

101

209

R.P.S

25

27

52

107

82

189

SINKAT

29

29

58

91

91

182

S.TOKAR

39

33

72

147

140

287

TOTAL

11

202

413

756

701

1457

There has been no significant increase in the percentage of the sample less than or equal to 75 cm in height since 1987 (figure 6.1).


Figure 6.1. Percentage of sample less than or equal to 75 cm in height, 1986, 1987, 1989.

Table 6.2. Ratios of males to females, nutritional surveillance Red Sea Province, 1989.

 

<=75 CM

>75 CM

DERUDEB

0.67

1.08

HALAIB

0.95

1.06

HAYA

1.17

1.03

N.TOKAR

1.43

1.07

R.P.S

0.93

1.30

SINKAT

1.00

1.00

S.TOKAR

1.18

1.05

TOTAL

1.04

1.08

There was no significant difference between the percentage of males and females in the sample. None of the ratios of males:females were significantly different from 1.00 (50% males, 50% females). In the samples for both 1986 and 1987 there was a significantly higher percentage of males than females.

2. Percentage of malnourished children (less than 80% reference median weight for height).

The percentage of malnourished children (less than 80% reference median weight for height) in the summa seasons of 1986, 1987 and 1989 by sex, district and for the total province, together with the 95% confidence interval for the population estimate, are shown in Table 6.3. These results are presented graphically in Figures 6.2, 6.3 and 6.4.

Table 6.3. Percentage of children less than 80% weight for height (malnourished) by district and for the total province, with 95% confidence Interval for the population estimate, children >75 cm.

   

CYCLE 3

CYCLE 6

1989

DISTRICT

 

MALE

FEMALE

TOTAL

MALE

FEMALE

TOTAL

MALE

FEMALE

TOTAL

DERUDEB

MEAN

28.15

22.76

25.58

15.74

28.40

21,16

15.00

10.75

12.95

 

CI

7.74

7.56

5.43

7.01

10.0

5.94

7.14

6.42

4.83

HALAIB

MEAN

11.61

13.45

12.55

6.45

9.28

7.89

16.50

12.40

14.50

 

CI

6.05

6.26

4.36

5.09

6.02

3.49

7.31

6.69

4.98

HAYA

MEAN

26.61

25.78

26.19

26.81

20.00

23.79

23.00

8.45

15.74

 

CI

7.94

7.73

5.54

7.54

7.63

5.41

8.42

5.59

5.19

N.TOKAR

MEAN

16.79

20.83

18.68

16.80

13.08

15.09

14.81

6.93

11.00

 

CI

6.39

7.41

4.86

6.69

6.58

4.70

6.84

5.05

4.33

RPS

MEAN

7.45

10.48

8.65

10.95

10.26

10.63

18.69

6.09

13.23

 

CI

4.14

5.97

3.45

5.34

5.61

3.87

7.54

5.28

4.93

SINKAT

MEAN

29.66

28.06

28.79

21.21

13.85

17.56

7.69

10.99

9.34

 

CI

8.41

7.62

5.65

7.12

6.06

4.70

5.59

6.56

4.31

S.TOKAR

MEAN

42.74

25.81

34.02

19.58

18.38

19.00

19.05

19.29

19.16

 

CI

9.15

7.86

6.10

6.64

6.64

4.70

6.48

6.67

4.65

TOTAL

MEAN

20.74

20.24

20.38

17.97

16.03

17.05

17.90

8.98

13.69

PROVINCE

CI

2.70

2.74

1.92

2.59

2.63

1.85

2.79

2.16

1.80


Flqure 6.2 Percent of sample less than 80% reference median weight for he/glut, summer season 1986, 1987, 1989. Males 75.1-115 cm in height.


Figure 6.3. Percent of sample less than 80% reference median we/glut for he/glut, summer season 1986, 1987, 1989. Females 75.1-115 cm In height.


Figure 6.4. Percent of sample less than 80% reference median weight for height, summer season 1986, 1987, 1989. Children 75.1-115 cm In height.

TOTAL PROVINCE: The percentage of malnourished children in the total province decreased significantly between 1987 and 1989. When the results were broken down by sex, however, the decrease in malnutrition was restricted to females. There was no significant decrease in the percentage of malnourished males between 1987 and 1989. In 1989 a significantly higher percentage of males than females were malnourished.

DERUDEB: The percentage of malnourished children in Derudeb has decreased significantly since 1987. When the results were broken down by sex, however, the decrease was found to be restricted to females. The percentage of malnourished male children has not changed significantly since 1987. In 1987 the percentage of malnourished females was higher than the percentage of malnourished males. The net result of the decrease in the percentage of malnourished females was that in 1989 there was no significant difference between the percentage of malnourished males and malnourished females.

HALAIB: The percentage of malnourished children in Halaib district was significantly higher in 1989 than in 1987. When broken down by sex, however, the increase was restricted to males. There was no significant difference in the percentage of malnourished females in 1987 and 1989. There was no significant difference between the percentage of malnourished males and the percentage of malnourished females in 1989. The percentage of malnourished children in 1989 was not significantly different from the percentage of malnourished children in 1986.

MAYA: The percentage of malnourished in Haya district has decreased significantly since 1987. As in Derudeb district, the decrease was restricted to females. The net effect in Haya district was that in 1989 a significantly lower percentage of females than males were malnourished.

NORTH TOKAR: There was no significant difference between the percentage of malnourished children in 1987 and 1989. The percentage of malnourished children in North Tokar had decreased significantly from the 1986 figures. There was no significant difference between the percentage of malnourished males and the percentage of malnourished females in 1989.

RURAL PORT SUDAN: There was no significant difference between the percentage of malnourished children in 1986, 1987 or 1989. When broken down by sex, however, the percentage of malnourished males was significantly higher in 1989 than in 1986. The percentage of malnourished females remained unchanged since 1986. In 1989 the percentage of malnourished males was significantly higher than the percentage of malnourished females.

SINKAT: There was a significant decrease in the percentage of malnourished children between 1987 and 1989. When broken down by sex, however, the decrease in percentage of malnourished children was found to be restricted to males. There was no significant decrease in the percentage of malnourished females between 1987 and 1989. In 1989 there was no significant difference between the percentage of malnourished males and the percentage of malnourished females.

SOUTH TOKAR: There was no significant difference between the percentage of malnourished children in 1987 and 1989. The percentage of malnourished children in South Tokar has decreased significantly since 1986. There was no significant difference between the percentage of malnourished males and the percentage of malnourished females in 1989.

The range of percentage of malnourished children between districts was smaller in 1989 than in 1986 and 1987. With the exception of South Tokar, no districts had a percentage of malnourished children that was significantly different from the province-wide mean in 1989. In South Tokar the percentage of malnourished children was significantly higher than the province-wide mean.

3. Health characteristics of malnourished children.

Diarrhoea and vomiting were the most frequently observed characteristics of poor health in malnourished children (Table 6.4). However, over 40% of all malnourished children had no outstanding health problems that could be identified by the field workers.

Table 6.4. Health characteristics of malnourished children (less than 80% reference median weight for height) In Red Sea Province.

Characteristic*

% of malnourished affected

No outstanding characteristic

40.7

Diarrhoea and vomiting

22.1

Fever

27.5

Anaemia

1.8

Mother dead

1.8

Mother anaemic

4.6

Mother has fever

6.8

Father dead

3.2

Father "sick"

1.8

"Sick from birth"

0.7

Skin disease

0.7

TOTAL

111.7**

* AS observed by field workers - no clinical or biochemical confirmation.

** Total more than 100% as some children displayed more than one characteristic.

4. Percentage of severely malnourished children (less than 70% reference median weight for height).

No significant difference was found between the percentage of severely malnourished males and severely malnourished females in any of the districts. No significant difference was found in the percentage of severely malnourished children between any of the seven districts. Aggregated province-wide results for the percentage of severely malnourished children are presented in Table 6.5.

Table 6.5. Percentage of children less than 70% weight for height (severely malnourished) for the total province, with 95% confidence Interval for the population estimate, children >75 cm by sex.

   

SEX

 

YEAR

 

MALES

FEMALES

TOTAL

1986

MEAN

2.28

3.73

3.00

 

CI

0.99

1.29

0.81

1987

MEAN

2.36

1.27

1.87

 

CI

1.03

0.80

0.67

1989

MEAN

2.19

0.62

1.44

 

CI

1.06

0.59

0.62

There has been no significant change in the percentage of severely malnourished males since 1986. Although there has been a steady decrease in the percentage of severely malnourished females between 1986, 1987 and 1989, this decrease was statistically significant between 1986 and 1987 only. In 1989 there was a significantly higher percentage of severely malnourished males than severely malnourished females. This is a reversal of the situation in 1986, when there was a significantly higher percentage of severely malnourished females than severely malnourished males in the total samples of cycles 1-3.

5. Health characteristics of severely malnourished children.

Table 6.6. Health characteristics of severely malnourished children (less than 70% reference median weight for height) in Red Sea Province, 1989.

Characteristic*

% of malnourished affected

Diarrhoea and vomiting

39.0

Fever

30.0

Anorexia and weakness

30.0

Not weaned (child over 18 months)

9.0

Whooping cough

9.0

Tuberculosis

4.0

Skin disease

4.0

TOTAL

125. 0**

* As observed by field workers - no clinical or biochemical confirmation.

** Total more than 100% as some children displayed more than one characteristic.

All severely malnourished children examined had one or more illnesses (although "anorexia and weakness" is a very general symptom which would be expected in all severely malnourished. Diarrhoea and vomiting and fever were the most frequently reported illnesses in severely malnourished children (Table 6.6).

6. Percentage of malnourished children <=75 cm in height.

As in 1986 and 1987, the highest rates of malnutrition in 1989 were found in children less than or equal to 75 cm in height (Table 6.7). These rates have not changed significantly since 1987.

Table 6.7. Percentage of ma/nourished children by height category, summer season, Red Sea Province 1986, 1987, 1989.

   

HEIGHT CATEGORY

 

YEAR

 

<=75 CM

>75 CM

1986

MEAN

39.74

20.38

 

CI

5.40

1.92

1987

MEAN

24.34

17.05

 

CI

4.14

1.85

1989

MEAN

25.09

13.69

 

CI

4.27

1.80

In view of the technical limitations of the data collection for children under 75 cm in height outlined in the previous paper, considerable caution needs to be exercised when interpreting these results. The nutritional status of children under one year old should, however, continue to be a cause for concern.

 

Conclusions

All conclusions refer to children 75.1-115 cm in height unless otherwise specified

1. There was no significant increase in the percentage of children less than or equal to 75 cm between 1987 and 1989.

2. There was no significant difference between the percentage of males and females in the sample in 1989. In 1986 and 1987 a significantly higher percentage of males than females were sampled

3. The percentage of malnourished children (less than 80% reference median weight for height) in Red Sea Province decreased significantly between 1987 and 1989.

4. At the province-wide level, the decrease in percentage of malnourished children was restricted to females. There was no significant decrease in the percentage of malnourished males in Red Sea Province between 1987 and 1989.

5. At the district level, changes in the percentage of malnourished children since 1987 can be summarised as follows:

Decreased significantly:

Females, Derudeb

Females, Haya

Males, Sinkat

No significant change:

Males and females, North Tokar

Males and females, South Tokar

Males, Derudeb Males, Haya

Females, Rural Port Sudan

Females, Sinkat Females, Halaib

Increased significantly:

Males, Halaib

Males, Rural Port Sudan

6. Diarrhoea and vomiting were reported frequently in malnourished children, although 40% of malnourished children had no concurrent illness that could be identified.

7. There was no significant change in the percentage of severely malnourished children between 1987 and 1989.

8. In 1989 there was a significantly higher percentage of severely malnourished males than severely malnourished females. This was a reversal of the situation in 1986.

9. All severely malnourished children examined had one or more concurrent illnesses, the most common of which was diarrhoea and vomiting.

10. As in 1986 and 1987, the highest rates of malnutrition were found in children under 75 cm tall. Although technical limitations reduce the validity of these results, the nutritional status of this group continues to be a cause for concern.

 

Discussion

It is encouraging that the province-wide rate of malnutrition has fallen significantly between 1987 and 1989. The province-wide percentage of malnourished children (13.69 ± 1.8) is below that at which Oxfam recommends general feeding (over 20% malnourished), but within the range of 10-20% malnourished children at which selective feeding programmes for vulnerable groups should be considered (Oxfam's Practical Guide to Selective Feeding Programmes, Oxfam Health Unit, 1984). Seasonality should be considered when interpreting these figures. They represent the percentage of malnourished children during the summer season, which has been shown to be the worst season with respect to malnutrition rates (see previous paper). It is likely that the percentage of malnourished children will decline further in the winter months.

For the first time since nutritional surveillance by Oxfam Port Sudan began, there was a significant difference in the percentage of malnourished children by sex at the province-wide level in 1989. The nutritional status of males was significantly worse than the nutritional status of females, both in terms of those less than 80% weight for height (malnourished) and those less than 70% weight for height (severely malnourished). This was due to a lack of improvement in the nutritional status of males between 1987 and 1989, whereas the nutritional status of females improved between 1987 and 1989. In those severely malnourished the situation of males and females has reversed since 1986. In 1989 significantly more males than females were severely malnourished, whereas in 1986 significantly more females than males were malnourished.

Interpreting the gender differences in nutritional status in Red Sea Province is difficult because of the absence of mortality data and reliable information on feeding practices and food intake. We could speculate that for whatever reason, given good rains and harvest, it is usual for the nutritional status of females to be better than that of males, and that the lack of difference in the nutritional status of males and females in 1986 and 1987 was because females bore the brunt of the food stress. The increase in the percentage of females in the sample to 50% in 1989 may indicate that female mortality in 1986 and 1987 was disproportionately high, an indicator of food stress. Alternatively, one or many factors may have prevented an improvement in the nutritional status of males, despite a general improvement in conditions. There may also have been an increase in male mortality, which would not be unexpected in view of the increased rates of severe malnutrition seen in males in 1989. Although we lack information to come to any sound conclusions for the causes of gender differences in nutritional status in Red Sea Province, it is obvious that gender is an important factor which must be considered in the future.

There was a smaller range in the percentage of malnourished children by district in 1989 than in 1986 or 1987. It appears that as conditions improve, variation in the nutritional status of children by district declines. Only Halaib district had a percentage of malnourished children which was significantly higher in 1989 than in 1987, although the figure was not significantly different from that in 1986. Two factors may have influenced the percentage of malnourished children in Halaib district in 1989:

1. The exceptional rains of 1988 did not extend into Halaib district.

2. Because of this, out migration from Halaib district to other areas may have been high in 1989, leaving a residual population of poorer families and/or the sick and elderly at the dumping points who then relied on food aid.

At the district level, three other results need to be highlighted as being of particular concern:

1. The continuing poor nutritional status of male children in Haya district.

2. The significant decline in the nutritional status of male children in Rural Port Sudan.

3. The continuing poor nutritional status of children in South Tokar.

The poor nutritional status of males in Haya and Rural Port Sudan districts is particularly important in view of the recent findings that over 50% of the population live in these two districts at some time of the year (ERGO Low Level Aerial Survey of Red Sea Province, 1989). The poor nutritional status of males in Haya represents a continuation of the situation found in 1986 and 1987. In Rural Port Sudan, however, the nutritional status of males has declined significantly between 1986 and 1987 despite the general province-wide improvement over the same time. There is no immediate explanation for the poor nutritional status of males in Haya and Rural Port Sudan. More information is needed to characterise malnourished males in these districts accurately. Haya and Rural Port Sudan districts would be good starting points for more detailed research on the causes of gender differences in nutritional status.

South Tokar district was the only district to have a percentage of malnourished children below the province-wide mean in 1989. Individual settlements in South Tokar had percentages of malnourished children as high as 53% (Garora town). This is a reflection of the continuing refugee problem in these areas, together with the lack of access of the Beni 'Amer to the grazing and agriculture which were rich after the rains of 1988.

There was no significant change in the percentage of severely malnourished children between 1987 and 1989, despite a decrease in the percentage of all malnourished children. This rate of severe malnutrition may be a "baseline level" caused as much by poor health conditions as by food stress. The high incidence of diarrhoea and vomiting in both malnourished and severely malnourished children highlights the need for co-ordinated preventive and promotive health care strategies to accompany attempts to reduce food stress. Forty percent of all malnourished children, however, had no identifiable concurrent illness at the time of the survey. As highlighted in the surveys of 1986 and 1987, more information is required about the functional significance of the 80% weight for height cut off in terms of health and development of children in Red Sea Province.

Despite the technical limitations associated with the measurement of children less than 75 cm in height, the continuing high rates of malnutrition seen in this height category should be a cause for concern and future investigation.

The Oxfam nutritional surveillance teams encountered continued strong resistance to the weighing and measuring of children. Ground teams for the aerial survey who were touring Red Sea Province at the same time reported seeing women and children running from settlements as their vehicle approached. On enquiring about this, they were told the women were hiding the children in case they had to be weighed. Apart from the bias that this introduces to the sample, it seems highly undesirable to enforce such obviously unpopular practices. This is not the type of relationship between the Beja and Oxfam which will enhance long term development efforts based on trust and open communication. The time has come to seriously investigate alternative forms of nutritional surveillance, or to abandon this line of research completely in favour of less invasive measures. There are no plans for further Oxfam nutritional surveillance in the immediate future.

 

 

7. Land tenure, agricultural labour, drought and food stress in the Gash, Gash Dai and Tokar agricultural areas. Roy Cole

 

Summary

Land tenure, agricultural labour, and the role of the Gash, Gash Die, and Tokar Deltas the Red Sea Province regional economy and in the food security strategies of the people of Red Sea Province is examined in the present paper. Results of the study show that sharecropping is a rational risk-minimising economic strategy that assures a food entitlement even in a highly variable environment such as that represented by the Tokar Delta and the Gash Dai. Where the environment is less variable, such as the Gash Delta, wage labour arrangements predominate. Both agricultural schemes were found to contribute significantly to the regional economy and to strengthen rather than weaken the ability of pastoralists to cope with drought through the provision of thousands of feddans of grazing, vast quantities of crop residues, cereals, and employment.

 

Introduction

The Gash Delta, in northern Kassala Province, and the Tokar Delta, in southern Red Sea Province, form two of the principal agricultural and livestock production areas of the Eastern Region (see Map 7.1). They are two of the richest areas in the Sudan. Other areas of great agricultural and pastoral importance in Eastern Province are Khashm el-Girba and Gedarif. The focus of the present report is on the Gash, the Gash Dai extension of the Gash Delta, and the Tokar Delta agricultural areas.

Although they are separated by three hundred kilometres, there is good reason to consider the Tokar and Gash deltas as part of one economic region. They share a common pool of labour and both are used as grazing areas by pastoral and agropastoral groups shuttling back and forth between Kassala and Red Sea Province. Both form a productive hinterland for large centres such as Port Sudan and Kassala and for small centres such as Tokar town, Garora, Derudeb, Haya, Sinkat, and Suakin. Until the 1970s, the Tokar and Gash Deltas were administered by the same authority. There was one manager, one plan, and one policy for both schemes. The system of administration changed when cotton was abandoned in the Gash.


Map 7.1. Agricultural areas, Eastern Sudan.

The Gash, Gash Dai, and Tokar agricultural and pastoral areas together constitute a resource for several classes of Red Sea Province residents as well as a resource for land users from Kassala Province, Eritrea, and the Nile Valley:

1. Landholders who reside in Red Sea Province but own land in one or more of the schemes.

2. Livestock owners who seasonally migrate with their animals, send their livestock with hired labour, or ship their animals by truck to one or both of the schemes during the course of the year.

3. Migratory and resident labour which seasonally moves from opportunity to opportunity or from home area to opportunity.

These three groups constitute a dynamic local system of sometimes contradictory interests linked to social, political, and economic structures at the regional, national and international levels. Although their interests may be sometimes contradictory in the particular, in general, however, they are mutually interdependent and must be in order to succeed and survive. All of the above groups attempt to minimize risk and optimize the return to their efforts.

In most years demand for labour exceeds supply in the Gash and Tokar Deltas. In the rainfall and flood deficit years in the early-1980s this situation was reversed. The 1989 agricultural year was a year of extreme labour deficit for the Gash for a variety of reasons most important of which was the abundant and well-distributed summer rains. These rains enabled people in Red Sea Province, for example, to plant in areas that they had not planted in six or more years. Indeed, some areas in 1989 were planted that had never been planted before, according to local accounts. This was the principal reason why many accustomed to annual work on the Gash stayed away this year, despite the higher wages. McLoughlin (1966) provides another interpretation of labour scarcity during wet years in the Gash. He states that for labour that is permanently resident in the Gash that in exceptionally wet years "...people who ordinarily would become labourers, planted their own crops (1966, 114)." Another important reason for the labour deficit was that the planted area in the Gash increased greatly because of the excellent rains and flood. There was simply too much work for the available work force. This year (1988-89) landowners have left sorghum stalks in the fields for the livestock because there is not enough labour to cut and transport them to market.

A last reason for the lack of labourers in the Gash Delta was the fear of disease. The incidence of malaria and typhoid fever in the Gash (but not the Tokar) Delta increased with the unusually high floods and rainfall and many labourers stayed away from the scheme.

Labourers in the Gash and Tokar schemes form part of wider familial and extrafamilial networks and employ economic strategies that include some or all of the following activities in differing proportions according to the time of year:

1. Urban wage labour.

2. Livestock raising.

3. Agriculture.

4. Rural crafts.

5. Gathering of marketable natural products.

6. Trade outside the auspices of the government

Labourers, when formulating an economic plan for a given year weigh the estimated relative benefits from all of the activities in which they are involved or are interested in becoming involved. When one economic activity appears to premise a good return, far example, agriculture in Eastern Region this year, the labourer will shift his or her economic activities to take advantage of circumstances. It is this opportunism that characterizes agricultural labourers in the two schemes.

Relations between the three groups mentioned above are decidedly market-oriented (see McLoughlin (1966) for a historical discussion of labour in the Gash and Tokar Deltas), but defined through customary arrangement. These customary arrangements generally involve same form of sharing of the agricultural products between the landowners, tenants, and labour force. There are many arguments for and against sharecropping in the Sudan and elsewhere (Mohammed M. Abdel Salam 1978, Elfatih Shaaeldin 1983, Mohammed Hashim Awad 1973). The view of the author, that traditional sharing arrangements spread risk in a highly variable environment and are superior to fixed rent systems is presented in the conclusion.

 

Production in the Gash and Tokar deltas

The Gash, Gash Dai, Tokar Delta and other planned and unplanned agricultural areas produce six categories of products:

1. Grain.

2. Sorghum or millet stalks.

3. Weeds.

4. Stubble and residual weed grazing.

5. Vegetables.

6. Fruit.

The first product from the schemes is grain, either sorghum or millet. The Gash Delta produces almost exclusively sorghum and the Tokar Delta produces more millet and sorghum. The principal variety of sorghum grown in the Gash is Sorghum bicolor; the specific variety is termed aklamoi. In the Tokar Delta Hijiiri sorghum and finger millet are grown. Grain yields in the Gash vary depending on soil type from ten to thirty ninety-kilogram bags per feddan according to our informants. According to Ausenda (1987), yields vary from between six and twelve ninety-kilogram sacks per feddan (almost 2 tonnes per hectare on average). In the present good year yields are reported to be high.

Systematic farming-system type studies need to be conducted in the Gash to improve our understanding of agricultural production and the links between agriculture and pastoralism. In the absence of such studies all figures must be treated with caution. Yields and prices in the Tokar Delta are comparable to those in the Gash. One half pound of grain is needed to seed a feddan at a spacing of 50 by 75 cm, the usual spacing in the agricultural schemes. Spacing of plants in Red Sea Province varies from 50 by 50 to 200 by 200 cm depending on site conditions.

In the Gash at Tindulai in January, 1989, a bag of sorghum was worth £110.00 Sudanese, however, at Delai Station, 100 kilometres north of Tindulai, it was worth £130.00, and in Port Sudan, £170.00.

Traditional grain flows from the Eastern Sudan are to Eritrea and the Arabian Peninsula (Paul 1954). According to reports, most of the grain produced in the Gash in 1989, as in most years, was sold in Eritrea because of the relative scarcity of grain there and consequent higher prices (£500.00 Sudanese per ninety-kilogram sack). In the past cotton was also smuggled in large quantities to Eritrea. Because of the illegality of unofficial exports, it is difficult to estimate the trade flows from the Gash and Tokar Deltas to Eritrea and Saudia Arabia. It is probable that Eritrea accounts for the major portion of the production of both schemes. It may also be that market shares are divided according to distance and price variables with the bulk of the Gash production going to Eritrea and much of the Tokar production to Saudia Arabia This is an unclear area

Traditionally, grain is stored in underground silos (matmuura, mataamiir) roughly 75 cm deep and 120 cm in diameter. Ten ninety-kilogram bags can be stored in each of these silos. Silos are dug separately or in swarms representing a family or several families of the same minimal lineage. The site is guarded by a family member who receives one small ruba' (3 kg) from each silo and one quarter of a ruba' from each person who adds to or removes from the stock. Ownership of production is by individual family and the guard keeps a list of all grain owners.

Sorghum stalks (millet and sorghum stalks in the case of Tokar Delta) are a second product of the agricultural schemes. Income from the sale of stalks varies from £100.00 to £300.00 per feddan depending on whether they are sold standing or cut and bundled. The value of sorghum stalks was another item that differed substantially from that found by Ausenda in 1986. Ausenda found that sorghum stalks per feddan were sold for £12.00 per feddan, a difference of a factor of ten; this is not easily explained by inflation.

A third important product from agricultural areas are weeds. In some years weeds may be more important than cultivated crops. Each feddan may produce up to 300 bundles of weeds (principally Echinochloa colonum and Cyprus rotundas). These bundles (kulega) are sold at £0.50 per bundle. This represents an income of up to £150.00 per feddan. This income is, as is income derived from the other sources mentioned above, variable.

The fourth product from agricultural areas is stubble and residual weed grazing. Outside the agricultural part of the Deltas (and in the Tokar Delta this means most of the delta itself) grazing on annual grasses (considered "weeds" on the scheme) is the principal use of the land. In many areas of the Tokar Delta these grasses remain green for up to nine months. They remain palatable for up to 3 to 5 years. Along the southern and eastern sides of Tokar Delta there are thick stands of Sueda fruticosa (adliib), excellent pasture for camels. In the Gash there is no adliib, however, pastures of annual grasses are plentiful and rich. Although it is difficult to evaluate the importance of stubble and residual weed grazing to the household and regional economies in money terms it is undoubtedly one of the major inputs to the livestock economy and is responsible for a large part of the weight gained and milk produced by livestock in and after the rainy season. The rest of the year is a period of weight loss for all livestock. This period of weight gain is of major importance for the survival of livestock in the dry season.

The fifth product from the schemes is vegetables. These are produced for home consumption as well as for the market. Although the distinction between food and cash crops is difficult to establish as most food crops are also cash crops the following division is useful. Market crops are tomatoes, watermelon, sorghum and millet, ful masry, beans (lubia and fasuuliya), spinach, cucumber, squash (courgette), carrots, okra, and greens. Crops that are used in home consumption are sorghum and millet, groundnuts and "sauce" crops like okra, greens, and squash.

A sixth product produced in the Gash, but not the Tokar Delta, is fruit. Small plantations of mango trees, orange trees, lemon trees, grapefruit trees and bananas are located along Khor Gash around the scheme area and reportedly all the way to Eritrea.

 

The Gash Delta

The Gash River originates in the Eritrean Plateau fifteen miles south of Asmara. It flows principally from July to September but there may be occasional flows in June. The length of flow of the Gash River from Kassala to the Gash Dai is about 160 kilometres. Average discharge is 560 million cubic meters of water. The highest annual flood was in 1929 when 1069 million cubic meters of water were recorded. The lowest flood years were 1921 and 1963 when the volume of the flood was 140 million cubic meters for each year.

Cultivation of cereals in the Gash Delta has probably been practiced almost as long as people have lived there. Little is known of the area prior to the nineteenth century. Cotton was first grown in the Gash Delta in 1870 by Mumtaz Pasha in the first experiment with cotton in the Sudan. The Gash scheme as it is known today began in 1924 with the cultivation of 9000 feddans. By 1927 over 26000 feddans were under cultivation. The total demarcated area of the Gash today is 720000 feddans although only 400000 feddans of this area are suitable for irrigation cultivation (Morton 1986). Only about one-tenth of the Gash area is used in any year for scheme agriculture. The rest is used for non-scheme cultivation or pasture. A network of seven main canals and thirteen subcanals are used to irrigate 240000 feddans in a three course rotation of 80000 feddans annually. Each of the three courses is fallowed for two years. The following table presents data on irrigated and cultivated land in the Gash during the twenty-six year span from 1963 to 1989.

Tab/e 7.1. Total irrigated area (scheme only), cultivated area, and area under sorghum (durra) in the Gash Delta, 1960 to 1988 (in feddans).

YEAR

TOTAL IRRIGATED

TOTAL CULTIVATED

DURRA

1960

12434

*

*

1961

22957

*

*

1962

12821

*

*

1963

37802

*

19364

1964

70852

*

25675

1965

49185

*

14810

1966

60593

*

14848

1967

103948

84197

40581

1968

45333

45333

13090

1969

80353

78470

29877

1970

80557

79341

35740

1971

86970

64167

28059

1972

74101

71275

33290

1973

72174

71935

30786

1974

100007

86816

42955

1975

159441

81319

59362

1976

61892

*

16393

1977

64593

62272

31762

1978

65278

54161

30425

1979

54446

49844

28740

1980

54951

26834

21623

1981

*

12861

*

1982

50184

35688

26330

1983

38358

*

32935

1984

51531

*

51531

1985

55371

*

55371

1986

46579

*

33288

1987

47000

*

29597

1988

78000

78000

78000

SOURCE: Gash Board (1989).

Cotton was the principal crop in the Gash until the early 1960s when it was gradually replaced by castor, first introduced in 1959. Prior to 1970, sorghum was sown over onequarter of the cultivated area, however, in 1970, when cotton cultivation was discontinued, the area devoted to sorghum increased to one-half of the annual area sown. The cultivation of cotton was reintroduced in 1976. The area sown to castor and cotton decreased from 1979 to 1984 and both crops were finally abandoned in favour of one hundred percent cultivation of sorghum in 1984. The Gash Board attributes the change in cotton cultivation to the following factors:

1. Declining yields.

2. Decline in international prices.

3. Cotton smuggling across the eastern border into Eritrea

4. Pest problems.

Factors cited by producers in the Gash in 1989 were:

1. Falling international prices.

2. Drought.

3. The high relative labour demands of cotton.

4. The inability to control destruction of cotton crops by livestock.

Castor was abandoned principally because of castor toxicity although decline in international prices was also an important reason. One independent economic study in 1987 found that castor production was a net loss to the producer.

There are 12000 registered tenant farmers on the Gash scheme in 1986, sixty-three percent of whom were Hadendowa Beja (Ausenda 1987). In 1929, seventy percent of the tenants were Hadendowa, according to Paul (1954). In 1988, according to the Gash Board, there were 14000 registered tenants and eighty percent of the tenants were Hadendowa According to Ausenda's 1986 figures, other ethnic groups that participate in the scheme are West Africans (23%), Other Beja (996), and Northerners (5%). Land is allocated on a firstcome first-served basis at an official rent of £16.00 per feddan. It was reported that some land is rented by the tenant to other tenants at rates of between £40.00 and £60.00 per feddan although this could not be substantiated.

According to the Gash Board, the tenancy is from five to fifteen feddans. Ausenda reports that individual tenancies may be as large as 700 feddans. According to Ausenda (1987: 122) each tenant is

...grouped into clusters represented by an 'agricultural sheikh'. All tenants are registered in the Corporation's books with a notation as to the size of tenancies assigned to them. The number of tenants, not the size of their tenancies, is prorated according to the ethnic group to which they belong. Each year, once lands destined to irrigation are flooded, they are allotted to all registered tenants according to a system based on the drawing of lots carried out in each of the six blocks into which the Gash Delta was divided.

The status of the Gash Dai is less clear than that of the Gash proper because it is outside government auspices and data are not regularly collected there. The total area of the Gash Dai is estimated to be 200000 feddans. Most of this area is used for pasture. Land is held in customary tenure arrangements by diwaab, a grouping of Hadendowa lineages. Landowning tribes in the Gash Dai come from the Derudeb, Musmar, Haya and Kassala areas. This year an enormous area was deeply flooded and consequently the planted area is unprecedented in size.

Organisation of labour

Beyond the level of the State, use of the land and its products in the Gash is organized into a two to three layered system.

1. The state.

2. The tenant (saahib al-rabt or saahib al-hawaasha).

3. The sharecropper (saahib al-tilt or saahib al-nuus).

4. The wage labourers (al-'ummaal).

The state is the landowner in the Gash Delta and it allots land in five to fifteen feddan parcels to tenants for £16.00 Sudanese per feddan. The state is paid a charge for irrigation and cleaning of the land at the end of the agricultural season.

The tenant, when a sharecropper is present, works under one of two arrangements:

1. When the sharecropper shares the costs of all stages of production he receives fifty percent and is called a saahib al-nuus.

2. When the sharecropper chooses not to share all costs of production he receives thirtythree percent and is called a saahib al-tilt.

Generally, the larger the tenancy or where the tenant is occupied with other activities (for example, his herds), the greater the likelihood of a sharecropper being present to manage the labour. On smaller holdings the tenant can manage the labour himself, providing that there are no other activities to divide his time. The tenant is responsible for the provision of seeds (fifty percent of the seeds if a saahib al-nuus sharecropper is present, one hundred percent if the sharecropper is a saahib al-tilt) and the food of the labourers (including coffee and sugar) for their period of contract in advance. The tenant keeps the sorghum stalks for himself. 1985 was the first year in which sorghum stalks were sent from the Gash to the Port Sudan market. Before 1985 sorghum stalks were just burned in the fields as a step in the cleaning of the field. An explanation advanced for this practice was that the government fined tenants who failed to have their fields clean by a certain date after harvest. It is more likely, however, that market prices for sorghum stalks were not high enough before the drought to encourage people to cut, bundle, transport and sell them.

The sharecropper is responsible for all agricultural activities including planting, weeding, replanting when necessary, harvesting, and the hiring and management of wage labour. Tenants or sharecroppers who need field labour go to the central market of Kassala to the wage labour market and hire those labourers that are needed. Unlike the Tokar Delta, there are no sharing arrangements for labourers; they are simply paid a daily wage. Contrast the arrangement used in Khor Arba'at in Rural Port Sudan in the production of tomatoes. There, the waterpump owner/landowner receives fifty percent of the proceeds from the sale of the tomatoes, the lorry driver to market receives twenty-five percent, the dealer in the market receives ten percent, and the producer-c of the crop fifteen percent. All of the people involved in production in the Arba'at area are generally related to one another. This is usually not the case in the Tokar and Gash Deltas.

There are 7000 to 10000 labourers working in the Gash Delta scheme at any one time (compared to 12000 to 15000 in the Tokar Delta). One fifth, or 1400 to 2000, of these labourers are tenants (Ausenda 1987) and the remainder are migrant labourers. Unlike other areas of Africa, most landlords in the Gash do not establish long-term relations with their wage labourers. Instead, they simply operate according to the laws of supply and demand and hire whoever is available at the lowest possible price.

Labour in the Gash area is organized and accomplished according to negotiated agreement (muqaawala) between the tenant and the labourers. Production is divided into five categories of activity:

1. Planting.

2. Weeding.

3. Cutting and piling sorghum heads.

4. Threshing.

5. Bagging.

By arrangement with the landlord these activities may be grouped. For example, cutting, threshing, and bagging may be negotiated together at a certain wage for one or more persons rather than three different persons. Specific rates depend on supply and demand. The following table illustrates wage rates in the Gash and Gash Dai for several activities.

Table 7.2. Wage rates In the Gash and Gash Dal In Sudanese pounds per feddan, January-February 1989.

 

Wage

Wage

Operation

Gash Delta

Gash Dai

Land Rent

16*

na

Planting

30

1/15 harvest

Weeding

50-100**

na

Harvesting

60

1/5 harvest

* £40.00 to 60.00 on the unofficial market

** Depends on degree of weed infestation

Quinney, in a report on the 1987 agricultural year, found workers to be paid £25.00 to 30.00 for weeding and £10.00 for planting. Ausenda (1987) reported £10.00 per feddan for harvesting during the 1986 agricultural year. If these data are accurate, then wage rates have doubled for weeding, tripled for planting, and, since 1986, increased six times for harvesting. There were rumours circulating in Eastern Region that harvest wage labourers in the Gash had negotiated a deal in which they received fifty percent of the harvest, although, I was not able to substantiate these rumours.

Harvesting, when combined with threshing and bagging as is the norm, is the most labour intensive agricultural activity; eleven days are required to harvest one feddan. Weeding requires 5.75 days per feddan and planting, the least demanding of all activities, only 1.5 days per feddan.

Generally, labourers prefer to work in the Gash Dai because, according to our informants, the remuneration was higher. Workers dislike daily wage labour. They prefer, instead, a sharing arrangement. No empirical evidence exists to prove or disprove the assertion made by labourers that sharing is more profitable to them than daily wage labour. This is a topic for future research.

Sources of labourers

Wage labourers originate from the following areas in order of importance:

1. South Tokar, Eritrea.

2. Khor Odi, Langeb, Baraka

3. Derudeb, Haya, Musmar, Sinkat.

4. Kassala

The first group is almost exclusively Beni 'Amer or Habaab, group two is Hadendowa, and group three is a mix of Hadendowa and 'Atman. The last group is composed of West Africans, "Nigerians" or, as they are commonly called, Takaariin and refugees. The West Africans in Kassala, and in the Eastern Sudan in general, are commonly called Fellata. This group is made up of many ethnic groups from western and central Africa. The word Fellata is of Kanuri origin ('Umar Al-Naqar 1972). Paul (1954) states that the original group of Kassala Takaariin (or Tarkarna, Takaariir, Tekruur, singular Tekruuri) made the pilgrimage to Mecca from Timbuktu in modern-day Mali in 1901 and settled in Kassala on their way home. The word "Takaariir" is said to come from the Arabic verb karrir, to repeat. The implication is that the West Africans termed Takaariin were pilgrims who sojourned in Red Sea Province two times, once on the way to Mecca and once on the way back. Another, more likely, explanation for the word is from the words "Tek Rur", a large region along the Senegal River valley. In Arabic this word becomes "Tekruuri". Tek Rur played an important role in the history of West Africa and particularly in its Islamisation and was the source of many pilgrims to Mecca ('Umar Al-Naqar 1972).

The Beni 'Amer group originates from two source areas: the mountains east and south of Kassala and a contiguous area composed of coastal and mountain South Tokar and northern Eritrea The principal source area in Eritrea is Barka Province, Eritrea's northerarnost and largest province.

Wage labour is the principal economic activity of most notably the Beni 'Amer and the West Africans. During the 1986 harvest in the Hadaliya block of the Gash, the Hadendowa accounted for 65%, West Africans for 25%, Eritreans for 10% of the wage labour force (Ausenda 1987). Hadendowa and West Africans are considered the best planters, West Africans are valued by landlords for their speed and thoroughness in weeding, and all groups are equally regarded with respect to harvesting (Ausenda 1986). Colonial officials used the numbers of West African labours on the schemes as an indicator of the relative prosperity of the agricultural year (McLoughlin 1966).

In the early part of this century, the majority of labourers presenting themselves for work in the Gash and Tokar Deltas were Eritrean Beni 'Amer or Habaab. These labourers selected between work in the Gash, Tokar Delta, or Italian construction projects in Eritrea depending on the relative wage rates in each area Interestingly, these Eritrean Beni 'Amer were of servile status (according to Nadel 1945 and Paul 1950) and "clients" (according to Ausenda 1989). They were liberated or released from their relationship with their masters, the Nabtab aristocracy, after the colonial conquest. Their liberation was due to the colonial powers need for a ready source of labour for the Gash and Tokar Deltas, although this point has not been established with certainty from the written historical record. One can infer from the behaviour of the colonial powers in other areas (Cole forthcoming).

The Beni 'Amer floating labour pool situated in South Tokar involved only in harvesting operations (cutters), appears to be less diversified, more proletarianised, and more vulnerable to economic stress than other groups of labourers. These people are of more recent immigration to Red Sea Province; many of them are war refugees. Most wage labour in the Gash and Tokar Deltas are of course poor, however, there is opportunity for surplus accumulation and social mobility for hardworking and enterprising labourers. The record of the more established Beni 'Amer immigrants is evidence for this. In the Gash, some individuals, as a result of hard work, may be allotted tenancies on the scheme. Others, after they build some capital, branch into market gardening of vegetables or watermelon. Many of the Eritrean Beni 'Amer who work in the Gash supplement their income by smuggling grain and sugar out of the Sudan to Eritrea by camel. It is difficult to estimate the volume of this trade because of its clandestine nature, however, the Ministry of Commerce in Khartoum estimated that 100000 tonnes were smuggled from the Gedarif area alone in 1977 (Simpson 1980). The demand for cereals created by war in recent years has probably augmented this figure.

Hadendowa labour migrants originate from the entire Hadendowa area in Red Sea Province. The Gash is but one of several stops on their annual labour itinerary. According to the Gash Board some Hadendowa, like other migrant labourers, work during the early season in the Khashm el-Qirba scheme or even as far south as Gedarif and later move to the Gash (see Bakhit (1988). Hadendowa also work in the Tokar Delta and McLoughlin (1966) suggests that the migrant labourers choose their workplace according to the wages being paid in shares or in cash.

Because of the political instability in Eritrea, and in the highlands in general, it is not uncommon to find highland Christians working in the Gash and in the Kassala area. These people are principally involved in the illegal importation and sale of alcohol from Eritrea If they are involved in agriculture it is generally with the cash crop, watermelon.

Most labourers in the Delta are involved in seasonal migration to other schemes in addition to their work in the Gash Delta. For example, planting and weeding are done earlier in Khashm al-Girba than in the Gash so that labourers begin the agricultural year on these operations in Khashm al-Girba. They proceed to the Gash to plant and weed and, depending on the size of the harvest, either return to Khashm al-Girba or remain in the Gash. If they remain in the Gash for the sorghum harvest they go to Khashm al-Girba for the cotton harvest after the sorghum harvest in the Gash is completed. Khashm al-Girba is a scheme developed in the 1960s for people displaced by the lake created by the Egyptian High Dam at Aswaan. Tenancies are divided between the displaced Nubians and people from the Shukriyya, Bishariin, Hadendowa, and 'Atman groups.

 

The Tokar Delta

The Tokar Delta is located in North Tokar District, Red Sea Province. The delta forms part of the Khor Baraka drainage system originating in Eritrea. The delta itself is about 500000 feddans in area, however, the actual cultivated area is far less. The northwestern side of the delta has not been cultivated since the 1940s when the main stream of the Baraka began moving east. The southeast side is uncultivated at present but soon will be under cultivation as the Tokar Board has been directing the flood in that direction since the early 1980s. At present, from 180000 to 200000 feddans in the central area of the delta are cultivable, although area cultivated depends on flooding and generally is much lower than this figure. Average area cultivated in the Delta is 140000 feddans, divided about equally between cotton and millet/sorghum. Cotton is considered the principal crop of the delta, however, there are large areas where cotton cannot be grown and millet and sorghum are grown instead. The major centre for millet/sorghum farming in the delta is south of Tokar town. In 1986, 67000 feddans of millet/sorghum were farmed in that area. Within the area devoted to cotton, millet is grown as a windbreak around each cotton plot as well.

The Tokar Delta is divided into seventy-nine areas of various sizes called a muraba'a Appendix 7.1). Each muraba'a is divided into rectangles of 160 feddans (800 by 800 meters). Each 160 feddan square is divided into sections of forty feddans divided by a road from east to west (al-arba'aiin) and from north to south (altamaniin). At each juncture of al-arba'aiin and al-tarnaniin there is a post indicating the location. A feddan in the cotton area of the scheme is divided into rectangles ten by fifteen meters in size and two rows of millet are planted along the edges of the entire area as a windbreak Cotton is planted in the centre of each block and three rows of sorghum (shawiir, shawaair) are planted between the blocks.

The average holding in the Tokar Delta is a topic of some controversy. Five years ago it was estimated to be about 12.5 feddans. The range of ownership is from one-half to 1000 feddans with the majority being in the less than five feddan category. Land ownership in the Delta is unclear, individual owners are unwilling to come forward and identify themselves. This situation may be ameliorated in 1989 because the Sudanese government has pledged £2000000 Sudanese to the landowners of the delta providing that they identify themselves, their tribal affiliation, and the size of their holdings.

Unlike the Gash Delta, land in the Tokar Delta can be bought and sold. A feddan of land near Tokar town, for example, can be sold for about £1500.00 Sudanese this year. The price reflects the quality of the land and the distance from Tokar town.

Organisation of labour

The land tenure system in the Tokar Delta developed differently from that in the Gash Delta Government involvement is minimal in Tokar and a three layered land use system is employed in contrast to the four layered system of the Gash Delta. This difference may be due to the greater interannual variability in the flood of the Baraka river and a risk minimisation policy adopted by the tenants and the Government (see below). The following table presents descriptive statistics on the difference in flooding between the Gash and the Tokar deltas. The table illustrates the point that although, on average, the Tokar Delta receives a greater flood, its interannual variability and consequent risk to the farmer is higher.

Table 7.3. Means, standard deviations and coefficients of variation for flooded area, Gash and Tokar Deltas.

Area

Mean

SD

CV

Gash

67580

25517

38%

Tokar

78120

39075

50%

* Dates are 1963 to 1988 for the Gash and 1963 to 1986 for Tokar.

Figures for the Tokar Delta for the years 1900 to 1987, since the beginning of the scheme, are as follows: mean, 67144; standard deviation, 41792; and coefficient of variation, 62.

The following table presents data on flooding and cultivated area in the Tokar Delta from 1900 to the present. Of particular note is the higher interannual deviation of flooding in the Tokar Delta as compared to the Gash.

Table 7.4. Joker Delta, total flooded and cropped areas and average yields In small qantars (100 Ibs), 1900 to 1987.

 

TOTAL

CROPPED

AVERAGE

TOTAL

CROPPED

AVERAGE

 

YEAR

FLOODED

AREA

YIELD

YEAR

FLOODED

AREA

YIELD

 

AREA

COTTON

sm Qantar

AREA

COTTON

sm Qantar

 

1900-1901

19068

2218

7.00

1946-1947

96000

52620

5.70

1901-1902

13369

307

3.70

1997-1948

65210

41580

8.00

1902-1903

14611

2641

7.00

1948-1949

26000

17565

4.20

1903-1904

18465

5273

5.50

1949-1950

56250

30265

3.50

1904-1905

39671

9487

5.00

1950-1951

168000

64340

5.30

1905-1906

33492

6058

6.10

1951-1952

38167

31997

2.10

1906-1907

36332

16397

5.00

1952-1953

50000

25000

4.30

1907-1908

50647

18005

5.00

1953-1954

134949

70000

4.80

1908-1909

27658

11048

4.80

1954-1955

27455

13482

2.40

1909-1910

45324

24655

4.00

1955-1956

2602

0

0.00

1910-1911

51287

39155

3.90

1956-1957

177873

100000

2.90

1911-1912

43923

29721

3.80

1957-1958

22165

15000

2.10

1912-1913

53495

22120

5.20

1958-1959

71787

44540

4.00

1913-1914

30061

11353

5.80

1959-1960

117721

79780

4.00

1914-1915

76598

30550

6.70

1960-1961

23485

6161

0.99

1915-1916

38154

10562

11.90

1961-1962

214838

123699

2.20

1916-1917

122661

44000

5.00

1962-1963

12491

7000

3.95

1917-1918

43190

19000

3.10

1963-1964

22685

12777

2.60

1918-1919

42670

21000

1.90

1964-1965

117435

53500

3.00

1919-1920

47797

30000

5.10

1965-1966

29000

11000

4.60

1920-1921

135977

70000

3.10

1966-1967

27000

17766

7.90

1921-1922

54914

31000

3.50

1967-1968

112000

85000

1.80

1922-1923

42000

21212

3.50

1968-1969

111000

25000

3.90

1923-1924

49863

33000

6.30

1969-1970

28000

14000

2.50

1924-1925

35000

22032

4.40

1970-1971

110000

47972

4.30

1925-1926

31000

14400

2.20

1971-1972

40000

22032

3.40

1926-1927

33900

20000

5.00

1972-1973

82525

44009

5.10

1927-1928

60000

45000

3.70

1973-1974

88546

30594

5.10

1928-1929

75000

50000

2.90

1974-1975

124641

56766

3.40

1929-1930

125000

95000

3.90

1975-1976

167000

64199

3.60

1930-1931

100000

60000

3.60

1976-1977

56000

11700

1.90

1931-1932

85000

38000

4.40

1977-1978

118000

6361

0.29

1932-1933

99000

44000

6.80

1978-1979

128000

22000

3.10

1933-1934

70000

37700

1.90

1979-1980

35953

13000

1.40

1934-1935

66000

31000

4.20

1980-1981

61213

14000

3.80

1935-1936

25000

14050

7.60

1981-1982

55680

20000

4.70

1936-1937

82000

43000

8.30

1982-1983

63535

15000

3.12

1937-1938

43000

20000

4.20

1983-1984

78315

25000

4.50

1938-1939

85000

40000

6.70

1984-1985

35000

10000

2.40

1939-1940

54000

27000

7.40

1985-1986

95000

25000

3.58

1940-1941

50000

33000

10.20

1986-1987

88358

30000

1.87

1941-1942

64000

25596

4.40

       

1942-1943

76000

33000

9.90

       

1943-1944

71480

20558

5.50

       

1944-1945

86000

42052

11.00

       

1945-1946

114000

47560

7.10

       

SOURCE: Tokar Delta Board.

The three strata that comprise the Tokar Delta system are:

1. The landlord (saahib al-dhimin).

2. The tenant (saahib al-nuus).

3. The labourer (saahib al-ruba').

The landlord is required to provide durra and vegetable seeds and pay for the digging of a well for drinking and vegetable cultivation. Cotton seed is provided free by the Tokar Board. The Tokar Board takes five percent from the proceeds of cotton sold for each landlord for the maintenance of the dike around Tokar town and five percent of the proceeds is taken by the District Council. The landlord is entitled to one-half of the harvest.

The tenant is required to clean and burn the field after the harvest and to manage the agricultural labour. He must provide the labourers with one meal a day. He is entitled to onehalf of the harvest. He divides his half with the hired labourers. Unlike the Gash Delta where labourers are paid in cash, in the Tokar Delta payment is made in kind according to negotiated shares of the tenants portion of the agricultural produce.

The tenant, like the sharecropper in the Gash, is found most often today on medium to large farms. His role is more akin to manager-shareholder than tenant. On small farms there is no tenant and agricultural labourers are free to negotiate the terms of their tenure. In this situation the landlord is responsible for cleaning the field at the end of the agricultural year.

The basic unit of agricultural labour in the Tokar Delta is the family. The male and female adult members of a family do the bulk of the agricultural labour and the children are expected to work from an early age and contribute to the household economy. Individuals who go to the Tokar Delta just to harvest are the exception to the above statement. They usually leave their families outside the Delta Each adult member of the family is paid separately. Children's wages are given to their father or guardian. The agricultural labourers are responsible for all agricultural operations except cleaning and burning the field for cotton, millet and sorghum, and vegetables. Men and women do the same tasks in general but women perform most of the cotton harvest. Women cannot work as much as men as they have responsibilities to the children. Women also look after the mink herd kept near the house. In general, women own part or all of these animals. In general, Beni 'Amer women invest their earnings in goats for milk and sheep for market, Fellata women invest in cattle, and Hadendowa women invest in she camels. Women from all groups invest in gold. Men generally invest in pack camels, cattle, and sheep for fattening for market.

The labourers have the right to the following:

1. Twenty-five percent of the actual grain harvest for sowing the crop (hence the name saahib al-ruba').

2. Twenty-five percent of the stalk production.

3. One-tenth of the harvest for harvesting the crop.

4. One-eighth for threshing the crop.

5. The second harvest from the regrowth from the stubble of the first harvest.

6. Twenty to twenty-five plasters for every pound of cotton picked.

7. One-third of the vegetable harvest.

For tomatoes there is a special arrangement made which sometimes works to the advantage of the tenant and to the disadvantage of the labourer. Ordinarily, consonant with the rules regarding vegetable harvest in general, the labourer gets onethird, the tenant gets one third, and the landlord gets one-third of the tomato harvest. The tenant, however, prefers if he can to squeeze out the labourer, who only plants the tomatoes, and take care of the tomato crop himself from planting to the hiring of harvesters. For example, suppose a box of tomatoes sells for £50.00 in Tokar town. Five pounds are paid to the people who pick the tomatoes and five pounds for transportation. The remainder is divided equally between the landlord, the tenant, and the labourer providing that the labourer planted the tomatoes. When the tenant eliminates the labourer at the planting stage he takes two-thirds of the proceeds himself.

Cotton is a special case as well. There are two seasons to the cotton harvest. The fast is during the bulk of the year when labourers are paid a fixed rate for each pound of cotton picked. After June 15, however, when livestock are permitted to graze freely in the Delta, wage rates rise dramatically almost to 50 percent of the sale price of the cotton. In May 1989 labourers were paid .20 plasters a pound or 5 Sudanese pounds per sack and 1 pound of sugar. After June 15th labourers were paid co plasters per pound. Of the sale price of 1.20 the landowner received .70 plasters. This time of the year is called the mustard period in the Delta. Some saahib al-ruba' hide their cotton until the arrival of this period in order to obtain higher prices. This activity is said to be common among most Beja tribes that use the Delta. The Beni 'Amer, however, are reputed to rarely engage in this practice. Generally, wives of labourers do the cotton picking.

The table below illustrates the change in harvest labour rates for cotton, tomatoes, and okra.

Table 7.5. Harvest labour rates in Tokar Delta for cotton, tomatoes and okra; 1980 to 1989.

YEAR

CROP

 

Cotton

Tomatoes

Okra

 

(£S/pound)

(£S/10 kg tin)

(£S/tin)

1980

.010

15.00

10.00

1981

.010

15.00

10.00

1982

.015

20.00

12.00

1983

.020

25.00

25.00

1984

.025

25.00

25.00

1985

.030

25.00

25.00

1986

.050

25.00

25.00

1987

.050

25.00

25.00

1988

.075

50.00

50.00

1989

.200

100.00

200.00

In years of drought the bottom may drop out of the labour market, as happened in 1985. In years of labour deficit, in contrast, the labourers may get more than twenty-five percent of the harvest as negotiated pay. With the twenty-five percent system, however, the labourers stand to make up to forty percent of the harvest when they perform the additional tasks mentioned above. The labourers are provided with one half of their subsistence for eight months of the year in the form of one meal per day, generally the midday meal. Lastly, the labourers have the right to the weeds in the field to use as fodder or for sale.

The share system is preferred by labourers to wage labouring. Wage labour in 1989 was paid at a rate of £25.00 per day in the Tokar Delta. There are two explanations why labourers prefer shares in kind to wages in cash. The first reason is that sharing is simply a better deal. This explanation is plausible enough especially considering the long list of benefits the sharer receives. This, however, does not explain the whole story. Another explanation for the preference for sharing has to do with the stranger status of the Eritrean Beni 'Amer, the majority of the labourers in the delta (see next section). Their political status in Red Sea Province is unclear; they have no rights and are not well regarded by local people. The Beni 'Amer claim that the Tokar Delta formed part of the Beni 'Amer territory before the expansion of the Hadendowa and minor tribes in the 17th and 18th centuries. Because of their present ambiguous status, these labourers prefer shareholding to wage labouring because it makes them appear to have more of a claim to the land (and, for those from Eritrea, Sudanese nationality) than do ordinary daily wage labourers.

Sources of Labourers

The principal source of labour for the Tokar Delta are relatively recent Beni 'Amer (Habaab) immigrants from Eritrea, local Beni 'Amer, Beja labourers from Red Sea Province (mainly Hadendowa), and West Africans. The Beni 'Amer are mostly permanent or temporary residents of the delta area residing on the outskirts of Tokar town itself, in Korayt, a controversial settlement located five kilometres to the northeast of Tokar towns, in the Ma'arafiit area, in one of the coastal settlements south of the delta, in the South Tokar mountains, or in Eritrea The West Africans live mainly in Tokar town or in Korayt and the Hadendowa come from coastal and mountain areas in North and South Tokar Districts as well as from Sinkat and Haya Districts. It was estimated by one informant that two thirds of the men who live along the coast between Tokar and Suakin migrate to the Tokar delta, either as labourers or just for the harvest. The harvesters, qaata'iin (cutters), go directly to the fields and begin cutting. At the end of the day each cutter presents his work to the tenant who apportions the shares. The Hadendowa from southeast and south central Red Sea Province go to Tokar only to harvest sorghum and return with their shares to their home areas. They are not interested in greater involvement in the scheme.

The labourers who live in and around the delta and who are on a one-quarter sharing system move to the fields in September to begin work. Their families follow them later, generally in November. They remain in the delta with their families for eight months until May or June. They take their milk and fattening animals with them to the fields to graze them. If they have many animals they send them to uncultivated parts of the delta for grazing. At the end of the agricultural year the labourers take most of their animals and enough fodder for three months with them to their settlements. Livestock holding as a form of investment is constrained in the Tokar system by limitations imposed by the amount of available fodder and space in the labourer settlements. Most of the labourers who have invested savings earned on farm in livestock send their animals to the South Tokar and Eritrean highlands in May or June for pasture. These animals return later in the year to graze on the scheme.

 

The schemes and food stress

It has been stated that, in general, precolonial society fared better in the face of environmental variation than it does today. More specifically, it has been said that the Gash and Tokar schemes have increased the vulnerability of people to the environment. I would like to address these two points below because I feel that these criticisms are unjustified

Precolonial relations between landowner and labour have been termed a "moral economy" (Watts 1983, Scott 1976) which cares for the vulnerable people during extreme food stress. Doubt has recently been cast on the general applicability of the "moral economy" model (see Bazin 1974, Ortoli 1939, Park 1971, Roberts 1980) and some researchers are now contending that the precolonial, premarket society was structurally incapable of coping with extreme food stress (Torry 1987). Watkins and van de Walle (1985: 10) state that "...most preindustrial economies were particularly vulnerable to crises." The authors suggest that these economies possessed production systems that had the following characteristics:

1. Few, if any, surpluses.

2. A lack of diversification.

3. A lack of systems of insurance and solidarity as have been developed by the modern state.

An almost continual condition of competition in the precolonial period between small, often ethnically different, groups reduced spatial mobility during periods of food crisis such that localized food shortages often became famines. The use of such formerly common droughtcoping strategies as the pledging of children to unaffected groups or individuals for grain has disappeared with economic diversification, increased mobility, and the cessation of intergroup conflict.

According to informants interviewed by Dahl just after the recent drought, Red Sea Province has had eleven periods of famine and loss of human and livestock life that occurred during the last one hundred and ten years (see paper 3 for a different interpretation of drought). The most severe instance of loss of life was during the 1880 to 1890 period when drought in conjunction with political instability and disease ravaged the population of Red Sea Province.

Table 7.6. Periods of food stress In Red Sea Province, 1880 to 1988.

YEAR

LOCATION

CAUSE

1880-90

General

Political instability, drought,

   

locusts, smallpox, cholera,

   

rinderpest

1904

Jebel Elba

Drought

1910

Atbai

Drought

1919-24

General

Decline of war demand and high

   

prices, high taxes

1925-27

General

Drought

1936

General

Drought

1940-42

General

Drought

1947-49

General

Drought

1955-58

General

Drought

1972

General

Drought

1979-85

General

D roughs

SOURCE: Dahl (1988).

It is important to note that the closer the period to the present the less important has been human mortality. Why, particularly during a time of general population growth, has this been so? Political stability, increased economic opportunity in the formal and informal sectors, spatial mobility have all contributed to easing the impact of environmental variation. The system of production used by Beja groups in and around Red Sea Province until very recently has been characterized by small surplus accumulation, lack of diversification, and no social insurance mechanisms to cushion extreme food stress. Indeed, one of the principal "mechanisms" for a group to cushion extreme food stress in the past was to transfer it to other groups by raiding or conquest.

The second point regarding food stress that I would like to address concerns the putative negative impacts of the Tokar and Gash schemes on the ability of the individual to respond to environmental variation. It has been stated by Morton (1986) and Ausenda (1987) that cultivation in the Gash Delta reduced pasture area and consequently caused a decline in herd size. Dahl (1988) states that the development of the Gash scheme involved a significant loss of grazing. The implication is that vulnerability to drought increased as a result of the schemes. These contentions are not supported by the facts as:

1. Much of the Gash and Tokar areas was impenetrable thicket prior to the development of the schemes and carrying capacity must have been low.

2. The majority of agricultural products produced today in and around the schemes, in particular stalks and weeds in the farmed areas and grazing in unfarmed areas, is destined to be consumed by livestock. The schemes are, in fact, fodder farms.

3. Water channelling and spreading techniques have increased the flooded area

4. The flooded, pasture producing, area is much greater than the cultivated area

In addition to producing fodder for local and transhumant livestock, the schemes produce fodder for export to predominantly Beja-owned feedlots in Port Sudan and towndwelling small stock owners in Derudeb, Haya, Sinkat, and Suakin. The feedlots in Port Sudan (located east of Daym al-wuhda) house approximately 12000 head of cattle which are used principally for the production of milk for consumption in Port Sudan and secondly as fattening stations for livestock for export. The feedlots, with the exception of some animals taken to local pastures during the winter rainy season on the coast, are entirely supported from outside. The history of the development of the feedlots since they began in the early 1970s is an interesting story of the successful adaptation of traditional activities to modem urban demand. The Gash and Tokar deltas are the breeding areas that produce the milk cows for the feedlots.

The argument that the Gash and Tokar schemes impede the ability of the Beja to cope with drought by making inaccessible traditional dry season pasture (or wet season pasture for that matter) is specious for the same reasons. The schemes have significantly increased grain production, fodder production, and have provided formal and informal sector employment for thousands of people and have, in fact, increased the ability of people to weather environmental variation successfully.

This is not to say that people are not having problems today or in the recent past - on the contrary, people have been impoverished by drought and inflation and there are large numbers of refugees in the province. These people gravitate to areas of opportunity such as the Tokar and Gash Deltas, the towns, and particularly Port Sudan.

A last point concerning vulnerability has to do with the sharing system versus the wage labour system. Sharecropping appears to be a form of risk sharing that works to the labourers' advantage. In good years the labourer is able to accumulate surpluses and in bad years is not liable for any fixed rent. Sen (1981: 5) has the following to say about sharecropping:

A peasant differs from a landless labourer in terms of ownership (since he owns land, which the labourer does not), the landless sharecropper differs from the landless labourer not in their respective ownerships, but in the way they can use the only resource they own, viz. Iabour power. The landless labourer will be employed in exchange for a wage, while the share-cropper will do the cultivation and own a part of the product. This difference can lead not merely to contrasts of the levels of typical remuneration of the two ... but also to sharp differences in exchange entitlements in distress situations. For example, a cyclone reducing the labour requirement for cultivation by destroying a part of the crop in each farm may cause some casual agricultural labourer to be simply fired, leading to a collapse of their exchange entitlements, while others are retained. In contrast, in this case the share-croppers may all operate with a lower labour input and lower entitlement, but no one may become fully jobless and thus incomeless.

Fixed rents appear to have a negative impact on the success of schemes to sedentarise pastoralists (Cole 1982). Variable rents enable the labourer to accumulate surpluses in good years as insurance against the inevitable bad years. In bad years the proportion of rent paid varies according to the harvest; in particularly bad years the sharecroppers are exempted from payment of their rents. This system, as opposed to fixed rent, seems to be well suited to the variable environment in Red Sea Province. For example, variation in flooding in Red Sea Province outside of the Tokar Delta generally varies by 100% from year to year. In the Gash and Tokar Deltas interannual variation is 38% and 62% respectively, much lower than all other watersheds in the Eastern Region.

Perhaps the difference between the Gash and Tokar deltas in terms of reliance on wage labour as opposed to sharecropping is that the Gash flooding is more reliable than that of Khor Baraka and the floods in the Gash Delta are supplemented by an average annual rainfall of 400 mm while in the Tokar Delta the average annual rainfall is 73 mm (see Cole 1989). It is possible that the Gash flow is more amenable to management than the Baraka The greater the environmental variation the greater the security demanded by labourers.

The present deterioration of the Sudanese economy is tragic because a healthy national and regional market economy in the Sudan is the short and longterm key to economic recovery for all Beja agropastoralists, farmers, and labourers in Red Sea Province. A strong and diversified regional and national economy and a strong national transportation infrastructure would promote successful adaptation to environmental variation. Strong economic performance would enable producers to accumulate assets, a diversified economy enables producers to find investments for their surplus, and a well-linked national infrastructure would enable individuals to move from opportunity to opportunity and to minimise risk through mobility. Without economic diversification it is clear that the ability of Beja pastoralists and agropastoralists to respond to drought will be seriously impeded.

 

References

Al-Naqar, U. (1972) The pilgrimage tradition in West Africa University of Khartoum Press, Khartoum.

Ausenda, G. (1987) Leisurely nomads: the Hadendowa (Beja) of the Gash Delta and their transition to sedentary village life. Columbia University Department of Anthropology, New York. 556 pp.

Bazin, J. (1974) War and servitude in Segu. Economy and Society, 2(3): 106-143.

Cissoko, S.M. (1968) Famines et epidemics à Tombouktou et dans la Boucle du Niger du XVI au XVIII siècle. Bulletin de l'Institut Français de l'Afrique Noire, B30(3): 806-821.

Cole, R. (forthcoming) Changes in drought-coping strategies in the Segu Region of Mali. Unpublished Ph.D. dissertation. Michigan State University Department of Geography, East Lansing, Michigan. 245 pp.

Cole, R. (1989) Drought, food stress, and the flood and rainfall record for Red Sea Province. Oxfam Port Sudan. 50 pp.

Cole, R. (1982) The sedentarization of pastoral nomads: an examination of 22 settlement schemes. Unpublished M.Sc. Thesis, Department of Resource Development, College of Agriculture and Natural Resources, Michigan State University, East Lansing, Michigan.

Cumming, D.C. (1937) The history of Kassala and the province of Taka, part one. Sudan Notes and Records, 20: 1-45.

Cumming, D.C. (1940) The history of Kassala and the province of Taka, part one. Sudan Notes and Records, 23: 1-54.

Dahl, G. (1988) Who can be blamed? Interpreting the Beja drought. University of Stockholm Department of Social Anthropology, Stockholm. 28 pp.

Elfatih Shaaeldin (1983) The Rist, Hashim and Imam reports: a resume. In Elfatih Shaaeldin (ed.) (1983) The evolution of agrarian relations in the Sudan. Ithaca Press, London. pp. 381-388.

McLoughlin, C. (1966) Labour market conditions and wages in the Gash and Tokar

Deltas, 1900-1955. Sudan Notes and Records, 47: 111-126.

Mohammed Hashim Awad (1973) Agricultural development in the Gezira Scheme: a rejoinder. In Elfatih Shaaeldin (ed.) (1983) The evolution of agrarian relations in the Sudan. Ithaca Press, London. pp. 389-395.

Mohammed M. Abdel Salam. (1978) Institutional impediments to developments in the Sudan Gezira scheme. In Elfatih Shaaeldin (ed.) (1983) The evolution of agrarian relations in the Sudan. Ithaca Press, London. pp. 357-379.

Morton, J. (1986) Oxfam Port Sudan and rural development in Red Sea Province: a discussion paper. Oxfam Port Sudan, Sudan. 31 pp.

Nadel, S.F. (1945) Notes on the Beni Amer Society. Sudan Notes and Records, 27: 51-94.

Ortoli, H. (1939) Le gage des personnel au Soudan Français. Bulletin de l'Institut Français de l'Afrique Noire, 1: 313-324.

Park, M. (1971) Travels in the interior districts of Africa in the years 1795, 1796, and 1797. Arno Press, New York.

Paul, A. (1954) A history of the Beja tribes in the Sudan. Cambridge University Press. Cambridge. 164 pp.

Paul, A. (1950) Notes on the Beni Amer. Sudan Notes and Records, 31: 222-245.

Quinney, S. (1988) Summary of work done regarding whether the food aid in RSP has deter,red people from seasonal work in the Gash Delta and Dai. Oxfam Port Sudan.

Roberts, R.L. (1980) Production and reproduction of warrior states: Segu Bambara and Segu Tokolor. International Journal of African Historical Studies, 13(3): 389419.

Sen, A. (1981) Poverty and famines: an essay on entitlement and deprivation. Oxford University Press, Oxford. 257 pp.

Simpson, M.C. (1980) Large-scale mechanized rain-fed farming developments in the Sudan. in Elfatih Shaaeldin (ed.) (1983) The evolution of agrarian relations in the Sudan. Ithaca Press, London. pp. 269-289.

Torry, W. (1987) Evolution of food rationing systems with reference to African group farms in the context of drought. In Glantz, M. (ed.) Drought and hunger in Africa: denying famine a future. Cambridge University Press, Cambridge. 1987. Pp. 323-348.

Watkins, S.C. and van de Walle, E. (1985) Nutrition, mortality, and population size: Malthus' court of last resort. In Rotberg, R.I. and Rabb, T.K. (eds.) (1985) Hunger and history: the impact of changing food production and consumption patterns on society. Cambridge University Press, Cambridge.

Zipf, G. (1948) The principal of least effort. Alfred Knopf, New York.

 

Appendix 7.1: Agricultural districts of the Gash Delta.

 

District

Area

Length of

   

(feddans)

Canals (km)

1.

Kassala

33000

27

2.

Mekali

42000

33

3.

Degain

33000

33

4.

Tindelai

48000

50

5.

Metataib

42000

31

6.

Hadaliya

42000

46

 

Appendix 7.2: Blocks (Muraba'a) of Tokar Delta.

1.

Mugdim

2.

Togwan

3.

Kalanda

4.

Trumbo

5.

Kulkul

6.

Titeeta

7.

Leaat

8.

Etteb

9.

Hilwa

10.

Haboi

11.

Aila

12.

Debba Salim

13.

Temnonai

14.

Gobal

15.

Illabilli

16.

Fattaka

17.

Alenlama

18.

Wadai

19.

Bardob

20.

Bawakneb

21.

Kurmin Neiu

22.

Burur

23.

Shaskeil

24.

Galateb

25.

Tankil

26.

Birgana

27.

Kalloteb

28.

Hashakau

29.

Kamageb

30.

Watawatia

31.

Bashatgaw

32.

Makrik

33.

Delawiay

34.

Wassir

35.

Abu Rish

36.

Trigdad

37.

Hasbub

38.

Mohammed Oar

39.

Mumtaz

40.

Selalat

41.

Abdullah Rai

42.

Tilil

43.

Tuteamab

44.

Tonak

45.

Fadda

46.

Adriameb

47.

Adai

48.

Shikibeb

49.

Kartut

50.

Bardadet

51.

Kugeriai

52.

Fardit

53.

Afafit

54.

Aweb

55,

Buruk Diblab

56.

Englim

57.

Mant

58.

Illadebbai

59.

Tifaeit

60.

Mifris

61.

Hirjan

62.

El-Watan

63.

Hagmug

64.

Barameiyu

65.

El-Ghaffar

66.

Galelama

67.

Basogeit

68.

Dambil

69.

Umbarki

70.

Sheraein

71.

El-Rowash

72.

Adam Addit

73.

Tabeinai

74.

Hamarit

75.

Nafisa

76.

Dang El-Habba

77.

Krimbit

78.

Mekiaf

79.

Bahr Era

 

 

8. Changes in tree density on five sites in Red Sea Province: early 1960s to 1989. Roy Cole

 

Summary

The object of the study was to determine the impact of human land use and drought on the density of trees in selected areas of Red Sea Province. five sites were examined during June and July 1989 for changes in tree density over the last 25 years. Density of trees was first counted from aerial photographs of the sites taken during the early 1960s then field work was carried out to determine the present density.

Tree density on the sites decreased greatly on three sites, decreased moderately on one site, and increased slightly on one site between the two time periods. Decline in tree density was due principally to human activities: charcoal and firewood production for market, land settlement, and land use intensification. Whatever impact recent drought may have had on the trees in the study sites was masked by human impacts. The author recommends that before any given land use development interventions are undertaken in Red Sea Province, research should be conducted to determine the long- and short-term environmental and social impacts of that development.

 

Introduction

The purpose of the present study was to assess the impact of increased resource use and drought on vegetation in five areas of Red Sea Province by comparing recent tree density counts with counts obtained from aerial photographs of the same areas taken twenty-five years ago. The tree is important to the dry season survival of all livestock in Red Sea Province. In many mountain, khor and delta areas of the province trees remain green throughout the year; these areas make up the dry season redoubt of pastoralism. Change in the densities of Red Sea Province's tree population has serious and long-term consequences for the pastoral system as a whole.

The issue of the human impact on trees is central to the present study in that, with the exception of a hypothetically severe and prolonged drought, the trees in Red Sea Province should enjoy a safe existence. The growth in human population, particularly Port Sudan, and the consequent increased demand for charcoal, firewood, kiln-fired bricks and pottery, bread, and building material has changed all this and traditional sanctions against destruction of the forest resource have been relaxed in principle and abolished in practice as the rural areas of Red Sea Province have been incorporated into Port Sudan's economic hinterland and structured to supply its needs.

Traditionally, the pastoral economy in Red Sea Province has been dependent upon two natural resources: annual and perennial vegetation. During the rainy, or flooding, season when protein-rich annual vegetation is available livestock make weight gains, reproduce, and provide the greatest quantities of milk. During the dry season when all vegetation except trees and some shrubs dies or dries up, livestock experience weight loss and low production. Any change in the availability of any of the pastoral resources in one season has implications for the survival of livestock in the other season and, if the change is severe enough, for the land use system itself. In some ways, perennial vegetation is more important than annual vegetation in Red Sea Province. When there is a drought and no annual pasture production, it is to the perennial vegetation that the livestock turn for survival. In the dry season, however, there is no alternative. If anything happens to impair dry season fodder production the pastoral system will be weakened.

 

Methods used in the study

Five sites in Red Sea Province were chosen to compare present tree densities with densities counted from vertical aerial photographs of the same sites at a scale of 1:40000 in the early 1960s. Map 8.1 below shows the distribution of the study sites around the province.

The first two sites were chosen because of their proximity to Port Sudan and urban demand. The third, fourth and fifth sites, on Khors Oko, Sitareb, and Nubahawayb were chosen for their distance from Port Sudan. The Khor Oko site is located on the other side of the Red Sea Hills northwest of Port Sudan in one of the most thinly populated, remote and arid parts of the Province. The Khor Sitareb site is located south-southwest of Port Sudan in a remote mountain valley on a minor tributary of Khor Sitareb. Site five, in a minor tributary of Khor Nubahawayb, is located on the western periphery of the Khor 'Udrus charcoal production zone west-southwest of Port Sudan. It should be emphasised that the study sites were not selected to be representative of the whole of Red Sea Province and any statements made in this paper refer only to the study sites.

Two criteria were used in selecting the sites from the 1:40000 photographs:

1. Individual trees had to be distinguishable on the photos but not too dense to cause clumping.

2. The location of the study sites had to be in areas where change in khor flow could not be responsible for changes in tree density. Expansive floodplains with wandering watercourses were avoided and sites were chosen in relatively narrow valleys where landforms controlled flow in a stable fashion.


Map 8.1. The study sliest

The trees were counted on the photographs using a 30X illuminated magnifying scope. In the field all vegetation was enumerated with the exception of the ubiquitous Indigofera spinosa and Aloe abyssinica on Site Five. In the calculation of density, however, only trees with a crown diameter greater than one meter were included because trees one meter or less in diameter were not visible on the aerial photographs. The minimum resolvable diameter was calculated by measuring railroad carriages on the photographs (2.5 by 11 meters) and comparing the measured distance with visible tree crowns. Annual or perennial ground cover, where occurring, was not enumerated as being not pertinent to the study.

 

The study sites

The Khor Akwaat sites

The Khor Akwaat sites are situated in middle Khor Akwaat above Sallum Station 30 kilometres southwest of Port Sudan in Rural Port Sudan District. For each site in Khor Akwaat we selected an area 1000 meters square. From each of these areas we selected three strips parallel to the Khor each 100 meters wide and 1000 meters long in which the trees were to be counted. The first, fourth and ninth strips were chosen to be measured; one strip on the edge, one in the middle and on the end of each block. At the Akwaat site the east-west dimensions of the study areas were found by measuring the distance of the telegraph poles along the railway. A Landrover was used to measure the north-south dimension. The map located on the following page shows the Khor Akwaat study area.


Map 8.2. The Khor Akwaat study site.

The Khor Oko site

The Khor Oko study site is located 170 kilometres west-northwest of Port Sudan on the western side of the Red Sea hills in Halaib District. This remote area is one of the driest in the region. Practically all vegetation is confined to khor beds and water lines. Because of the relatively low density of vegetation and its homogeneity along Khor Oko, a 500 square meter block was chosen randomly from the aerial photographs of the vegetated course of Khor Oko. A 1:250000 false-colour Landsat image was used to locate the study site in the difficult terrain and the 1:40000 photograph of the study area was used to define the location of the site more precisely. The dimensions of this site were measured with ropes 500 meters in length. The map on the following page shows the Khor Oko study area.


Map 8.3. The Khor Oko study site.

The Khor Sitareb site

The Khor Sitareb study site is located on the eastern side of the khor on a minor tributary near the source of Khor Sitareb. This site is 140 kilometres south-southwest from Port Sudan in North Tokar District. A strip 500 meters long and 100 meters wide was chosen from the 1:40000 photographs as the Sitareb study site. The site is located along the east bank of the tributary and extends 500 meters to the west. The 500 meter long strip was divided into 5 onehectare squares using ropes and the trees were counted on a hectare by hectare basis. Map 8.4 on the next page illustrates the situation of this site.


Map 8.4. The Khor Sitareb Study site.

The Khor Nubahawayb site

This site is located on a minor tributary of Khor Nubahawayb. It is located 115 kilometres west-southwest of Port Sudan in Rural Port Sudan District. A study area of 2 hectares was chosen from this minor khor, transecting it at the point just before it leaves the mountains to join sandy Khor Nubahawayb and the sandy 'Udrus basin. The map on the following page presents the site in detail.


Map 8.5. The Khor Nubahawayb study site.

 

Results

Change in tree densities on the five sites varied; for three sites the change was dramatic and negative, for one site change was moderately negative, and for one site change was slightly positive. The greatest differences were for those sites closest to Port Sudan. The following table presents the counts from the aerial photographs and ground observation for all five sites.

Table 8.1. Tree counts on five sites In Red Sea Province, 1960s and 1989.

Site Percent

 

1960s

6/7 1989

 

Change

1. Khor Akwaat Site One

Line 1 293

47

-246

-84

Line 2 279

95

-184

-66

Line 3 252

136

-116

-46

2. Khor Akwaat Site Two

Line 1

274

0

-274

-100

Line 2

246

0

-246

-100

Line 3

228

123

-105

-46

3. Khor Oko

54

36

-18

-33

4. Khor Sitareb

108

112

4

4

5. Khor Nubahawayb

159

139

-20

-13

Table 8.2 below presents a summary of the site results and an additional variable, distance from Port Sudan.

Table 8.2. Percent change In tree density, early 1960s to 1989, by site and distance from Port Sudan.

Site

Percent

Distance from

 

Change

Port Sudan

Sites One and Two

-59

30

Site Five

-13

115

Site Four

+4

140

Site Three

-33

170

 

Khor Akwaat

As is evident from Table 8.1, there have been some dramatic changes in tree density and distribution in the Akwaat study area since the early 1960s. All of this change has been negative.

Average density for Site One dropped 66 percent during the 25 year period The drop in Site Two over the same period was 84 percent. The decrease in density was not distributed equally over the three lines of each site. There was an 84, a 66, and a 46 percent decrease in the tree densities of lines one, two and three respectively of Site One. The change for Site Two was dramatic for lines one and two. These lines each decreased 100 percent. Line three decreased 46 percent.

In 1963 the trees were denser near the khor and became less dense with distance from the khor. In Site One at that time density dropped 13 percent from lines one to three. In Site Two as well, density dropped 17 percent from lines one to three. In 1989 this situation was reversed. Although overall density declined throughout the transects, the relative density of trees today is greater with distance from the khor. Line one in Site One in 1989 contained 65 percent less trees than line three. In Site Two the difference between 1963 and 1989 was 100 percent less. The figures below illustrate these differences.


Figure 8.1. Tree densities on site one in 1963 and 1989.


Figure 8.2. Tree densities on site two In 1963 and 1989.

Khor Oko

The site in Khor Oko had a 33 percent decline in tree density from the 1965 to 1989. The following figure illustrates both distributions.


Figure 8.3. Tree densities on site three In 1965 and 1989.

Khor Sitareb

The pattern of vegetation change at the Khor Sitareb site was one of slight increase. The figure below presents the densities for both periods.


Figure 8.4. Tree densities on site four in 1965 and 1989.

Khor Nubahawayb

Tree density declined modestly on site five. The figure below presents the results for this site.


Figure 8.6. Tree densities on site five In 1965 and 1989.

 

Conclusion

Substantial negative changes in the density of trees were measured on three study sites. a moderate decrease was found on one study site, and a slight increase was found on one study site in Red Sea Province. The cause of the decline in tree density is probably related more to human activities than drought, however, the effects of drought were impossible to measure given the degree of change attributable to human land use activities.

 

Discussion

There is no area in Red Sea Province in which the resources are not used in some way by people From local firewood consumption, local firewood and charcoal production for export, village bakeries, to the Tokar wood-fired brickworks, the demands made on: natural- resources in Red Sea Province are great and are increasing as population grows. The marginal nature of the physical environment of Red Sea Province presents limitations to unremitting use.

The results of the present study (see Vetaas 1989 for similar results from elsewhere in the province) suggest that where human impacts are low there may be little change in tree density since the 1960s. Negligible impacts are clearly associated with remote areas and low human and livestock populations Changes in tree densities and the agents and processes of change will be discussed: in the section below. The study sites will be treated in the same order as they were presented above.

Khor Akwaat

There are three related processes responsible for the decline in tree density in the areas studied in Khor Akwaat.

1. Urbanisation.

2. Land settlement.

3. Agricultural intensification..

Urbanisation

Urban demand has existed in the area for a long time. It is likely that residents of Suakin cut trees in Khor Akwaat in recent centuries. Greatest urban demand, however, has come most recently since the Second World War and particularly during the last twenty years from Port Sudan. It was during the last twenty years that a market-oriented firewood and charcoal infrastructure based on the souk lorry developed.

Since that time, Khor Akwaat has become a source area for fuelwood and the principal linkage to the Khor 'Udrus and Agwampt basins, two of the most important sources of charcoal in recent years for Port Sudan.

A possible explanation for the change in the expected relative density of trees with distance from the Khor Akwaat in Site One may be the practice of "high-grading" commonly employed in harvesting timber and minerals elsewhere in the world. Highgrading is a form of the economic principal of least effort which under the present circumstances involves harvesting the most valuable tree species first. Areas where density is highest and trees are biggest are the first to be harvested. This type of practice is the least costly in time and effort. Trees in Red Sea Province are typically biggest and densest near the khors where water is more freely available. This suggests a possible reason for the change in relative densities.

Land settlement

The first settlement of the area began in 1910 with the establishment of a religious centre (khalwa). The establishment of khalwas in the Sudan was in private hands until the 1920s when the British instituted Indirect Rule through the Powers of Sheikhs Ordinance (1922). The objective of this ordinance was to replace the effenditype of administration based on the Egyptian model with rule by the indigenous elite (Holt and Daly 1979). Construction of subsidised secular schools was stopped in 1922 and a policy of subsidising khalwas was adopted in its place. In 1918 there were 8 subsidised khalwas in the Sudan. By 1930 there were 768; an increase of 9600 percent.

In 1906 the colonial administration built a railroad from Khartoum on the Nile to Port Sudan via 'Atbara. Port Sudan was opened in 1909 to replace Suakin, the old Turkish trade centre on the coast, sixty kilometres to the south of Port Sudan. In 1924 the rail link was built from Khartoum to Port Sudan via Kassala joining the 'Atbara line at Haya junction. About 50 railway towns were founded in Red Sea Province where there had been no permanent settlement in the past (see Collins and Deng 1984). Many of these railway towns have developed into small centres and a few into towns. The last leg of the Khartoum to Port Sudan railroad is located in Khor Akwaat and two railroad towns were founded in the coastal valley of Khor Akwaat. One of these railroad towns, Adar Awayb Station, is still insignificant but the other, Sallum station, has grown into a minor centre. The line from Sallum station to Suakin was dismantled after the Second World War.

Agricultural intensification

The most devastating influence on vegetation on the Khor Akwaat site has been, however, not urban demand for fuelwood or settlement, but rather the wholesale clearance of land for vegetable gardening. Most of the clearance has taken place during the last three years. Two thirds of Site Two are today part of a garden belonging to the Horticulture Department of the Ministry of Agriculture, one of the first gardens established in Khor Akwaat ten years ago. In 1963 there were no gardens or cultivation of any sort in the area at all. Three years ago it was discovered that Khor Akwaat had greater than expected subsurface water supplies and a high demand was created for areas in which to garden to supply the Port Sudan market. The Port Sudan vegetable market is supplied at different times of the year by production in the Wad Medani area, Kassala, Tokar, and Khor Arba'at. It was this last area that provided the model for market garden cultivation in Khor Akwaat. Khor Arba'at is located only twenty kilometres northwest of Port Sudan and can be considered to represent local production. The major differences between the two areas are:

1. Surface and subsurface water supplies at Arba'at are much more abundant than at Akwaat.

2. Land is being sold to people from Port Sudan who are interested in establishing market gardens in Khor Akwaat.

It is possible that the land clearances in the Khor Akwaat area were sparked more by a speculation scramble than by any serious study of the real potential of the area for sustainable agricultural production. The National Water Corporation's branch office in Port Sudan, for example, states that there is definitely not enough water to garden at the present level of gardening and continue to supply Port Sudan with water. Although it was known before the scramble that subsurface water was available in the area, it was not known how much or what quality of water lay beneath the soil. Well digging costs are considerable especially when it is not at all certain that the well will be wet and sweet. Last year, a new landowner had a bore hole well drilled and found only saline water. At a cost of 125000.00 Sudanese pounds per bore hole this is not a cheap mistake. Since the time this well was dug a damper has been put on well digging in the area, however, people are still buying land, clearing it, and erecting fences.

According to field estimations between 15 and 20 square kilometres have been cleared but not cultivated in any way at the time of the present study, June 1989. Most of this clearance has taken place during the last two years. A feddan of land at the time the study took place cost 1000.00 Sudanese pounds, about 35.00 pounds Sterling at the unofficial exchange rate or 125.00 pounds Sterling at the Business rate. In November 1989 the price had risen to 2000.00 Sudanese pounds per feddan.

It is surprising that the Beja landowners are selling their land. The Beja are wellknown to defend their territorial rights, sometimes violently, against the claims of others. The Hadendowa-Rashayda dispute in Kassala is a famous case in point. The Beja in general are willing to permit others to use their land providing that the user make no ownership claims to the land. In the present case, the people who had traditional rights to the land in Akwaat have long since moved to Port Sudan and have little interest in the area The principal purchasers of land in Khor Akwaat are AfroArab "northerners" from the Nile Valley who have settled in Port Sudan, since the beginnings of the British colonial administration in the Sudan. The author made some discreet enquiries about purchasing some land in Khor Akwaat and he was told to address any requests to the 'Umda

Khor Oko

Unlike the sites in Khor Akwaat, Khor Oko is remote from urban demand for fuelwood, however, similar forces are at work there. The major impact on vegetation in Khor Oko has been the settlement of pastoralists in khalwas, religious settlements, during the last 40 years. The sedentarisation movement is associated with the mosque of Shariif Adarob in Tumaala located about 35 kilometres south of the study site. In an effort to raise the productivity of the areas where religious settlements were established, seasonal watercourses have been diverted and water impounded for fruit tree, vegetable, and sorghum production. The fruit and vegetable production is destined for the Port Sudan market. In Tumaala and its satellites, wood is used in cooking and heating (during the relatively cold mountain winter) and in the construction of houses. There are at least two wood-consuming bakeries in Tumaala.

Before the establishment of the religious centres in the area, herders had no fixed address. Their housing was made from light palm mats, easy to pack up and move from place to place. The environmental impacts of such herders was spread over space. The rationale for the pastoral economy in such a marginal environment was continual movement throughout the seasons for fodder and water.

Today, in contrast, people have settled with their animals along Khor Oko. The people in the area live in houses made of tree trunks, although some families live in palm mat tents surrounded by tree trunk fences. The tree trunk house is characteristic of religious settlements in Red Sea Province. Each house is from 5 to 10 meters in length and 5 meters in width. A log frame is constructed and the tree trunks are planted vertically in the ground and made to lean against the frame. The trunks are piled upon one another in layers and from 150 to 200 trunks are needed to build one house. The principal source of tree trunks is Khor Oko.

The links between the Tumaala area and Port Sudan are increasing. The Naqaseb pass, northwest of Port Sudan was built through the mountains in the late 1970s in order to facilitate exchange between Port Sudan and the Nile valley. Communication was only by camel before the pass was built.

In an area as environmentally marginal as western Red Sea Province, certain costs must be paid for settlement and the increased intensity of land use. A familiar pattern of land degradation is appearing around these settlements. For 30 kilometres east of Tumaala, the main settlement in the area, along Khor Hayet, all dead wood has been removed. One sees an occasional stump belonging to a live cutting. From 30 kilometres from Tumaala to just east of the Naqaseb pass, dead wood is plentiful and there is no evidence of the fuelwood trade. Just a few kilometres east of the pass, however, there is no more dead wood and stumps are plentiful. This is the catchment area of Port Sudan today (see Map 8.6).

Khor Sitareb

The Khor Sitareb site was the only site studied that had an increase rather than a decrease in tree density. An increase occurred on 2 hectares of the 5 hectares examined, although slight decreases occurred on the remaining 3 hectares. The two hectares that had. an increased tree density are located on the edge of the study strip, from the main flow of the khor. Use of the area for fuelwood production has been low. There were no chopped trees or evidence of live cuts. There were randomly-distributed dead trees and branches in the area, an indication of slight use for commercial as well as domestic production. The area is remote and outside of the fuelwood production zone of Port Sudan. What fuelwood is produced in the area goes to Tokar town, 25 kilometres southwest of the site. The production in upper Khor Sitareb, however, is minor and peripheral to the Tokar. The area has no road links to urban areas. Land use on the Khor Sitareb site can be said to be negligible. The density distribution of the trees on the site are what one would expect in a semi-arid area - higher densities closer to the water courses: density and size are a function of the availability of water (see Figures 8.7 and 8.8). This is markedly different from the results for Khor Akwaat where tree densities actually were found to decline as moisture availability increased!

An interesting contrast to the case of upper Khor Sitareb is Khor Dahant located' 35 kilometres due north of Khor Sitareb. There is an oil refinery in Port Sudan linked by a pipeline to Khartoum. This pipeline passes through Khor Dahant. A pumping station to pump the oil over the coastal mountains is located just below the mountains. This pumping station is linked to Suakin by an improved road. Because the road makes transportation easy and cheap the fuelwood of Khor Dahant is economic to cut, process into charcoal, and send to the Suakin and Port Sudan markets. With increasing linkage this will be the case of upper Khor Sitareb as well.

Khor Nubahawayb

The Khor Nubahawayb study site is located in a minor tributary of Khor Nubahawayb on the western edge of the 'Udrus charcoal production area It is located 3 kilometres from the Port Sudan to 'Udrus/Agwampt charcoal transportation route. The changes in tree density observed probably are due to charcoal production although some domestic consumption may be involved. No dead wood was seen in the area There were several chopped and mutilated trees and evidence of charcoal making. This area is on the- periphery of the most important charcoal producing zone for Port Sudan in Red Sea Province, the 'Udrus Basin. Substantial amounts of charcoal also come from Khor Agwampt to the west of the study area. In contrast to the other study sites, charcoal production has been the major process affecting trees in this area. There is no permanent settlement in the khor but a permanent dwelling has been built there to shelter herders and their animals when they pass through.

The major source of demand for charcoal in this area is Port Sudan. Demand from Sinkat, 45 kilometres to the south, has increased in the last few years with the improvement of the Sinkat-'Udrus road and mountain pass, however, demand from this town is minor compared to demand from Port Sudan.

One can imagine an outward-moving frontier of urban influence that began radiating from Port Sudan soon after the Second World War, structuring the rural economy. It has been during the last twenty years, a period of high urban growth, however, that the greatest influence of Port Sudan has been felt in the rural areas. As demand for fuelwood in Port Sudan grew the trees in the immediate areas were cut and transported to market. As local supplies were exhausted producers went further afield. Two economic zones developed around Port Sudan. In the first zone it is profitable to cut and transport wood to Port Sudan. In the second zone, more distant than the first, it is profitable only to produce and transport light weight to value charcoal to Port Sudan.

Charcoal and firewood production is commonly said to have increased during and after the drought in the early 1980s in Red Sea Province. Fuelwood production during and after that time became a survival strategy among many, the most popular being urban migration and agricultural employment on the agricultural schemes in and around the province. A drought relief programme intended to assist the recovery of the people of Red Sea Province extended and refined the transport infrastructure of Red Sea Province during the mid-1980s and had an indirect effect on charcoal and wood production by extending and making transport easier. During the course of this four-year programme an average of 5 lorries were sent about every three months to 410 food distribution points located around the province. This represents one distribution point for every 1000 rural people in Red Sea Province.

Although local transportation was important in the transportation of charcoal and wood in the past (Paul 1954, Newbold 1935, Sandars 1933) traditional modes of transportation do not appear to be significant in the delineation of these production zones except for very local transport of fuelwood, for example, branches or logs from Khor Arba'at by donkey or camel to Port Sudan. In almost all cases traditional transport has been incorporated into the modem transport structure. Donkeys and camels supply remote bulking points served by souk lorries supplying Port Sudan. The model is distorted by modern factors that ease the friction of distance. The domination of the industry by the souk lorry has already been mentioned. Another factor, the levelling and paving of the way from Port Sudan to Kassala and Khartoum in the early 1980s has extended the zone in which it is profitable to transport local firewood to Port Sudan and extended the local charcoal profitability zone as well. A souk lorry is capable of carrying a 7 to 7.5 tonne load. This represents 200 bags of charcoal per lorry. Charcoal can be purchased at 35 Sudanese pounds per bag at Tugalhuush, the first bulking point east of the 'Udrus charcoal production zone, and sold in Port Sudan for 110 Sudanese pounds. The cost of one lorry load of charcoal at Tugalhuush is 7000 Sudanese pounds and the sale value in Port Sudan in June 1989 minus transportation costs is 20000 pounds. This sum represents 1100 pounds Sterling at the official exchange rate or 800 pounds Sterling at the black market rate. The following figure illustrates the relationship between charcoal prices and distance from Port Sudan in June and July 1989. The June figures are prior to the enactment of price controls in the urban areas and the August figures reflect the new policy of urban price control after the change in government on 30 June 1989. The following figure presents charcoal prices per 40 kilogram sack at three bulking points along the Port Sudan-Udrus basin charcoal transport route. Also included in the figure is the change introduced after the July change in government. It does not appear that the change will have any impact on the charcoal producers except in cases where production is integrated with marketing. For example, where a lineage produces, transports, and markets the charcoal in Port Sudan. In this case there will be a substantial loss of income at the Port Sudan level.


Figure 8.6. Charcoal prices per 40 kilogram sack at three bulking points located 30 to 80 kilometres west of Port Sudan and at the market In Port Sudan, June and July 1989.

The following map presents a general view of the fuelwood production zones around Port Sudan.


Map 8.6. Fuelwood production zones for Port Sudan, Red Sea Province.

 

Limitation of the study

Chief among the limitations of the present study is that we were unable to visit more sites. Several reasons were responsible for the time constraints that forced us to limit the scope of our study. first among these was staff unrest leading to lengthy negotiations that had to be resolved before worn could be started A second reason was the delay in the arrival of our computer equipment to analyse and map our results. Related to reason one is that we did not have the time or resources to collect data representative of the entire province. Statements made about vegetation in this paper refer only to the study sites themselves and must not be extrapolated to other areas. A last limitation concerns the resolution of the aerial photographs. Some error may have been caused by our inability to resolve trees less than or equal to 1 meter in diameter. This may have biased our counts of trees on the photographs downward since two adjacent trees, each one meter in diameter, would be distinguishable only as one tree. In this case, the results of the study are more disturbing.

 

References

Cole, R. (1989) Land tenure, agricultural labour, drought and food stress in the Gash, Gash Dai and Tokar agricultural areas. Oxfam Port Sudan.

Collins, R.O. and Deng, F.M. (eds.) (1984) The British in the Sudan, 1898-1956. Macmillian Press, London. 258 pp.

Kassas, M. (1956) The mist oasis of Erkowit, Sudan. Journal of Ecology, 44: 44-194.

Hall, P.M. and Daly, M.W. (1979) History of the Sudan: from the coming of Islam to the present day. Weidenfeld and Nicolson, London. 250 pp.

LeBon, J.H.G. (1965) Land use in the Sudan. Geographical Publications Limited. Bude Cornwall, UK.

Newbold, D. The Beja tribes of the Red Sea hinterland. In Hamilton, J.A. (ed.) The AngloEgyptian Sudan from within. Faber and Faber, London.

Paul, A. (1954) A history of the Beja tribes of the Sudan. Cambridge University Press, Cambridge.

Sandars, G.E.R. (1933) The Bisharin. Sudan Notes and Records, 16(2): 119-149.

Vetaas, O.R. (1989) Biotic and abiotic factors in the secondary succession in Erkowit, Red Sea Province. Proceedings from a workshop of the Red Sea Area Programme (RESAP), Khartoum, January 1989.

 

Appendix 10.1. Charcoal dealers by quarter and size class, Port Sudan, August 1988.

QUARTER

 

FREQUENCY OF OCCURRENCE

 

House

Small

Medium

Large

Giant

TOTAL

Abu hashiish

1

1

1

2

0

5

Al-asklila

0

0

1

0

0

1

Al-marghanlya

21

11

13

0

0

45

Al-wuhda

4

10

4

0

0

18

Dar al-na'im

3

13

12

9

0

37

Dar al-salaam

18

22

6

5

0

51

Daym al-'arab

23

9

1

0

0

33

Daym al-madiina

1

1

0

1

2

5

Daym al-nuur

10

25

15

3

3

56

Daym al-ramla

0

7

4

0

0

11

Daym al-shaty

0

0

0

1

0

1

Daym jaabir

1

2

2

0

0

5

Daym kuriya

2

4

5

4

0

15

Daym mayu

1

6

5

5

0

17

Daym muusa

0

3

8

9

0

20

Daym salalab

14

21

13

5

0

53

Daym takaariin

0

2

4

0

0

6

Hai phillip

2

3

1

2

0

8

Hai walli

7

8

7

4

0

26

Main souk

4

5

0

0

0

9

Ongwab

6

2

1

0

0

9

Ras al-shaytaan

1

2

4

0

0

7

Salabuna

3

2

1

0

0

6

Sikka al-hadiid

1

1

0

1

0

3

Tarab hadal

0

0

3

1

0

4

TOTAL

123

160

111

52

5

451

The following size class definitions of dealers were used:

CLASS

NUMBER OF BAGS OF CHARCOAL

 

Min

Max

House

1

3

Small

4

20

Medium

22

100

Large

110

700

Giant

1200

2200

 

Appendix 10.2. Total stock of charcoal per class of dealer by quarter, Port Sudan, August 1988.

QUARTER

 

NUMBER OF SACKS (40 kg)

 
 

House

Small

Medium

Large

Giant

TOTAL

Abu hashiish

3

8

90

380

0

481

Al-askiila

0

0

35

0

0

35

Al-marghaniya

34

101

736

0

0

871

Al-wuhda

8

100

155

0

0

263

Dar al-na'im

5

193

705

2080

0

2983

Dar al-salaam

26

202

303

1200

0

1731

Daym al-'arab

25

81

40

0

0

146

Daym al-madiina

1

5

0

380

3400

3786

Daym al-nuur

17

256

723

1600

5300

7896

Daym al-ramla

0

79

160

0

0

239

Daym al-shaty

0

0

0

140

0

140

Daym jaabir

3

35

55

0

0

93

Daym kuriya

4

38

303

1570

0

1915

Daym mayu

1

50

250

1400

0

1701

Daym muusa

0

33

475

2875

0

338

Daym salalab

22

177

530

1300

0

2029

Daym takaariin

0

17

375

0

0

392

Hai phillip

5

44

70

220

0

339

Hai walk

12

112

288

1305

0

1717

Main souk

7

44

0

0

0

51

Ongwab

7

20

55

0

0

82

Ras al-shaytaan

3

17

275

0

0

295

Salabuna

3

12

90

0

0

105

Sikka al-hadiid

2

20

0

200

0

222

Tarab hadal

0

0

135

500

0

635

TOTAL SACKS

188

1644

5848 15150

8700

31530

 

 

Appendix 10.3. Some characteristics of charcoal production and trade.

There are three interesting characteristics of the charcoal trade in Red Sea Province:

1. Local production is considered inferior to charcoal imported from the Gedarif area

2. Local production supplies only a small part of the Port Sudan demand.

3. Production of charcoal and especially firewood in Red Sea Province is a poor person's occupation.

The best charcoal in Port Sudan is imported from Gedarif. The charcoal making process used in the Gedarif area is better than that used in Red Sea Province and the charcoal is of higher quality. In addition, individual pieces of Gedarif charcoal are bigger than charcoal made from Red Sea Province's small acacias. Although transport costs are reflected in the higher price of Gedarif charcoal, higher quality is also involved').

The fuel of preference among the upper and aspiring classes in Port Sudan is bottled gas. Bottled gas burns cleaner and, most important, is subsidised by the government. A full bottle costs only 16 Sudanese pounds. Most families that use gas use charcoal on occasion as well. The charcoal ES used for specialty cooking, for example, coffee, or at large gash--rings where gas would be impractical to use such as weddings. Gas is in such demand that there is a thriving black market in gas bottles and regulators. An empty gas bottle currently sells for 1500.00 Sudanese pounds. Since the change in government of 30 June 1989 and the imposition of price controls in urban areas, the cost of locally produced and imported charcoal has dropped dramatically from 110 and 140 to 55 Sudanese pounds per 40 kilogram sack; a 50 and 61 percent drop respectively. People who previously principally used bottled gas are now switching to charcoal. In July 1989, all of the charcoal in stock in Port Sudan was sold within a week after the beginning of price control.

 

11. Conclusion

In the present collection of papers we have presented research results (and have discussed the results of others) on a variety of research topics conducted in Red Sea Province including environmental variation, environmental degradation, economic instability, political instability and the regional economy at the macro level, and age and gender in relation to malnutrition and drought-coping strategies at the micro level (see Figure 11.1 on the next page).


Figure 11.1. Macro trends and processes and Micro conditions that affect the ability of an Individual or group to respond to adversity.

The figure above illustrates the interaction and feedback from the micro to the macro levels. By Level of Development is meant the level of development of the transportation infrastructure, the level of urbanisation, the availability of urban employment, the presence of opportunity associated with agricultural schemes, et cetera. By Economic Instability it is meant economic inflation, the highly variable performance of local and international prices, and the general economic condition at the national and regional levels regarding employment and economic investment. By Political Instability, war, banditry, and lack of national political integration if that lack of integration has destabilising effects at the regional or local levels are meant. By Location (at the micro level), the degree of isolation is meant; distance from towns or agricultural schemes. By Economic and Social Opportunities, personal or family wealth, special group membership, education, and skills are meant.

More research needs to be done at the micro level to contribute to our understanding of the impact of all of the variables mentioned above. Continued macro level monitoring of the economy and the environment are necessary as are studies of environmental change in order to help us understand more fully the wide mix of variables that condition the ability of individuals and groups to respond to adversity. Some of the papers have provided new tools and frameworks of analysis that could be useful in other studies.

Although the research presented in the present collection of papers has contributed much to our understanding of drought, drought response, and recovery in Red Sea Province, many questions remain. It is hoped that the research currently planned, underway, or nearing completion by the Environmental Research Group Oxford and the Universities of Bergen and Khartoum will add more to our understanding of the area.

The general picture that emerges from our studies is positive in some respects but negative in others. People are recovering from drought in Red Sea Province. The nutritional status of children is getting better. Rains and floods have been good and even exceptional over the last few years and livestock populations are increasing. Greater links are being forged between the rural and urban areas and drought-coping strategies are becoming more diversified. A worrying problem, however, is the impact of people on the environment of Red Sea Province and the costs to the pastoral and agricultural economy that this represents. This may increase the vulnerability of people who depend on these resources in the future.

 

Some comments on Oxfam and research

The research conducted by Oxfam Port Sudan over the past two years has been very much an experiment. The Research Section at Oxfam Port Sudan was created to fill the gaps in our knowledge about the Beja, drought, response, and recovery. Synchronic views were avoided in all of the studies that make up this collection because without a clear understanding of the past there is no means to interpret the present or future. It is this point of view that has been at the heart of the research programme in Oxfam Port Sudan.

Oxfam's research experiment in Red Sea Province has produced rewarding results. Research is essential if Oxfam is to make sound policy decisions and evaluation is necessary to maintain a credible level of accountability. It has been useful to have one person continuously present to organise and coordinate the research. It would have been more appropriate, however, for a Research Officer to have been appointed at the beginning of Oxfam's involvement in Red Sea Province to give continuity and consistency to the work.

There are two types of research that Oxfam can support: programme research and relief related research. These two types of research may be conducted by local nongovernmental organisations, government, or by Oxfam itself.

At the programme level, three types of research are necessary in development to help ensure a successful outcome. The first type is conducted before a programme begins. The second type is ongoing. The first type of research is generally termed programme identification or needs assessment. Ordinarily this work is done in a cursory fashion. Identify the place, what can be accomplished there in general terms, who benefits, and some guidelines on how to go about accomplishing the identified objectives. The second type of research is designed to augment the knowledge of the programme team after the programme has begun and enable the team members to accomplish the objectives articulated in the programme identification paper or to tailor those objectives to something more realistic. The third type of research at the programme level is more properly termed evaluation. This evaluation determines if the programme itself achieved its stated objectives in the manner intended. This evaluation can be ongoing (formative evaluation) or occur at the end of the programme (summative). Ongoing evaluation is more desirable because it modifies the programme as it develops and should be incorporated at the planning level. Oxfam programmes should not be approved if they do not provide for ongoing evaluation at the planning stage.

Research in relief programmes is and has been more problematic than that associated with development programmes. Usually, emergencies are such that a quick response is called for rather than lengthy consideration about the merits of involvement; evaluation has rarely been considered as a priority, although there is evidence that this is changing. When outside intervention moves from the camps to the general population research must be conducted to determine the necessity and the economic, social, political, and environmental impacts of such action. In relief programmes professional evaluation is of the greatest importance. It is essential that Oxfam require an ongoing research and evaluation component be incorporated at the planning stage of every relief programme.

A final point is whether Oxfam is the right organisation to be doing research. It may be more appropriate for the national government, local government, local universities, or local nongovernmental or professional organisations to conduct research. Local institutions may be able to conduct research in greater harmony with local people, local institutions and government than is possible by an outside organisation. A possible role for outside organisations may be in training researchers. This type of effort will enhance a country's human resources and strengthen institutions rather than create parallel structures on a temporary basis.

 

 

Technical glossary

There are two kinds of statistics:

1. Descriptive: used to organise and summarise data.

2. Inferential: based on probability theory and used to make educated guesses about a population based on information obtained from a sample of the population.

A brief description of each statistical method used in the reports is given below.

Descriptive statistics.

1. Average, or measure of central tendency.

The average is a general term used to describe where the central or most typical value of a data set lies. There are three measures of centrality, or the average.

i. The mean. The mean is the sum of the data divided by the number of pieces of data. It is the preferred measure of central tendency for continuous (metric) data providing there are not large numbers of very big or very small values. This is the most commonly used measure of central tendency.

ii. The median. Defines a number which is the dividing point between the top 50% of the data and the bottom 50% of the data Used mostly with ranked or ordered data on a scale (ordinal data).

iii. The mode. The value that appears most often in the data set, which might not be the middle in any sense. Used most often for qualitative data.

2. Measures of dispersion.

A measure of dispersion is a number used to show how much variation exists in a data set around a central point.

i. Sample standard deviation (s or sd). Deviation refers to deviation from the mean (an individual value minus the mean value). The average (mean) of these deviations is then calculated. The more variation there is in a data set, the bigger the standard deviation. In any data set, almost all the values fall within three standard deviations either side of the mean.

ii. Coefficient of variation (CV). This expresses the standard deviation as a percentage of the mean.

Inferential statistics.

Inferential statistics are based on probability theory. A brief description of each of the statistical teens used in the report will be given here. Details of the theory and calculations involved can be found in several basic textbooks (see below).

1. Statistical significance. A level of probability which is set as a cut off point for determining if differences between two populations are due to some determining factor, or whether they are due to sampling error or chance. The conventional level for this probability (p) is 0.05. The differences are accepted as being due to some determining factor only if the same results would happen by chance less than 5% of the time. We are 95% sure that the results are not due to chance.

2. Z scores (zee scores!). Z scores are calculated by subtracting an individual value from the mean value for the sample, and dividing the result by the standard deviation for the sample. Z scores are standardised scores. Raw data are transformed into a form in which many different types of data can be directly compared on the same scale. This scale is expressed in terms of standard deviations from the mean, and can also be used for calculating the probability of certain scores or proportions of scores occurring by chance. In the population 68% of z scores will be between -1 and 1 9596 will be between -2 and 2, and 99.7% will be between -3 and 3. The closer a Z score is to zero, the closer it is to the mean.

3. Confidence intervals. A confidence interval is a range of values &round the sample mean within which we can be reasonably confident that the true population mean or proportion lies, based on information taken from a sample of the population and probability theory. "Reasonably confident" usually is taken as 95% confident. A confidence interval can be constructed for the differences between means or proportions also. If this confidence interval includes zero, it is probable that there is no true difference between the populations. If the confidence interval does not include zero it is probable that differences between the populations are due to some determining factor other than chance.

4. T-tests. Tests the (null) hypothesis that two samples come from two populations with the same mean and differ only because of sampling error. Requires the sample size, mean and variance to be known. T-tests assume that the variances in the two populations being compared are equal.

5. One way analysis of variance (ANOVA). Used to test for simultaneous equalities between groups of means, based on two variance measures: one to measure variance within the groups being compared, and one to measure the variance between the groups being compared. These two measures are compared using the F-test. It answers the question "is the variability between groups large enough in comparison with the variability within groups to justify the inference that the means of the populations from which the different groups were sampled were not the same?" If it is determined that the groups being tested are not simultaneously equal, further tests are required to pinpoint exactly where these differences occur (post hoc tests). ANOVA can tell us how much of the variation in one variable is explained by its interaction with another.

6. Simple correlation. Measures the degree of linear, or "straight-line", relationship between two variables. It may be positive (direct) or negative (inverse). It is expressed as a correlation coefficient (r) which is between -1 and 1. If the correlation coefficient is 1, all data points lie on a straight line with a positive slope. If the correlation coefficient is -1, all data points lie on a straight line with a negative slope. A correlation, however strong, does not imply causality. Inferences about correlations in the population can be made from the sample correlation. Significance testing can tell us whether the correlation coefficient is too big or too small to provide useful information. Different methods of calculating correlation coefficients can be used depending on the characteristics of the data being investigated.

7. Regression.

a. Simple regression. Where correlation describes the strength of a linear relationship between two variables, simple regression describes the form of this relationship and allows us to make predictions about how values outside the sample will behave. Using simple regression it is possible to determine to what extent change in one variable influence change in another variable.

b. Multiple regression. An extension of simple regression which is widely used for determining the relationship between one outcome variable and a combination of two or more predictor variables. This technique is particularly useful for examining complex data sets where one outcome variable (such as percent weight for height) may be influenced by many other predictor variables (ranging from age to mother's education, for example). A model of how all these predictor variables best fit together to explain changes in the outcome variable is produced.

8. Factor analysis. A complex technique for analyzing patterns of common variation, or intercorrelation, among many variables and isolating the dimensions to account for these patterns. Factor analysis describes the patterns of correlation between many variables in terms of a relatively small number of common factors. It is particularly useful for generating new hypotheses about the relationships between variables.

Suggested reading:

Weiss, N. and Hassett M. (1982) Introductory Statistics. Addison-Wesley Publishing Co. Inc. Reading, Massachusetts.

Isaac, S. and Michael W.B. (1983) Handbook in Research and Evaluation for Education and the Behaviourial Sciences. EdITS publishers, San Diego, California.

Sage University Paper Series on Quantitative Applications in the Social Sciences. Sage Publications. Beverley Hills, California.

Concepts and Techniques in Modern Geography (CATMOG) series, Geo Abstracts, University of East Anglia, Norwich.

World Health Organisation (WHO) (1983) Measuring Change in Nutritional Status. WHO, Rome.