Environmental Engineering Reference
In-Depth Information
ecosystems (Coe et al., 1976; Kundhlande, 2000). However, if the analysis
is to be accurate, it is essential that this relationship is estimated as pre-
cisely as possible. Data may therefore be required to estimate this relation-
ship for a particular ecosystem or study area.
In this example, primary data would therefore be required of the input
and output variables given in Equation 11.13. With the exception of the
data on rainfall, these data could be obtained through a questionnaire
survey of the local population answering the following type of questions:
Crop production data:
1.
Do you own or rent land?
2.
What is the total size of your land holding?
3.
What do you produce on your land?
4.
What was the total amount you produced of each crop last year?
5.
What is the total amount of seed you sowed last year for each crop?
6.
How many people were involved in caring for that crop and for how
many hours did each work?
7.
Did you apply fertilizer to any of your land? If so, what type of ferti-
lizer, to which crops, and how much?
8.
Did you irrigate your crops with groundwater? If so, how much water
was used?
It should be noted that again this illustration gives an example of the kinds
of questions that should be asked in a questionnaire survey, but not of the
form the questions should take.
In addition to this data, the level of rainfall must be known for the study
area. To make a comparison over time, two dif erent approaches can be
taken: either the survey can be longitudinal, that is, carried out over a
number of years, or cross-sectional, that is, carried out at the same time
but over a number of dif erent study sites. This will then provide variation
in the data of rainfall and the other inputs into production. A simplii ed
example of the results of such a study is given in Table 11.2 using only
three inputs, rainfall, labour and land area, and three study areas.
To identify the quantitative relationship between these variables, a
multiple regression analysis can be carried out using the quantity of crop
produced as the dependent variable and the input data as the independent
variables. The results of the multiple regression for this example are given
in Equation 11.14.
Q
5
W
0.7
L
0.2
A
0.1
R
2
5 1
(11.14)
