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close this book Measuring drought and drought impacts in Red Sea Province
close this folder 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
View the document Summary
View the document Introduction
View the document Methods
View the document Results
View the document Conclusion
View the document Discussion
View the document Limitations of the study and comments on the research method
View the document An alternative method
View the document References

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.