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close this book Measuring drought and drought impacts in Red Sea Province
close this folder 3. Drowght, food stress, and the flood and rainfall record for Red Sea Province. Roy Cole
View the document Summary
View the document Introduction
View the document Precipitation In Red Sea Province
View the document Flood and rainfall records: problems and possibilities
View the document A definition of drought
View the document The flood record
View the document Drought and the flood record
View the document The rainfall record
View the document Drought and the rainfall record
View the document Conclusion
View the document Discussion
View the document Limitations of the study
View the document References
View the document Appendix 3.1. Annual floods for nine khors In Red Sea Province and Khor Gash in Kassala Province.
View the document Appendix 3.2. Annual flood 2 scores for nine khors in Red Sea Province and Khor Gash in Kassala Province.
View the document Appendix 3.3. Annual rainfall in mililmetres for 19 gauging stations in eastern region, Sudan.
View the document Appendix 3.4. Annual rainfall z scores for 19 gauging stations in eastern

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.