Environmental Engineering Reference
In-Depth Information
consequently, wrongly formulated objectives. In other cases, it might be due to the
unsatisfactory quality of the data obtained, as result of unadequate laboratory quality
control. This question is much more valid for developing countries, which face acute
social and economical problems and hardships. Therefore, they need to prioritize the
problems and their solutions. Understandably, diffuse pollution problems lack priority.
The importance of water resources for the development and well being of any country
need not be overemphasized, but for the countries in the region, water is a scarce resource
and its importance is essential in terms of sustainable development. Numerous documents
and publications deal with water-related issues from different perspectives. Only as an
example, we could mention Turton et al. (2003), a publication discussing problems
associated with the governance and management of the Okavango River basin. Even the
best visions and intentions, reflected in different policies and strategies, could fail to
achieve a sustainable use of water resources for the development of the country or the
region, if sufficient and reliable information with respect to water quantity and quality is
not available. Such type of information could not be borrowed or adapted from other
sources, because of the specifics of each geographical region and the level of social and
economic development. Therefore, it needs to be collected, stored and used in this
specific location. Only a well-designed monitoring program could provide for such
information. In addition, water quantity and quality parameters are randomly varying in
terms of time and spatial frame; therefore, continuous and regular monitoring is essential.
In numerous cases in the region, information with respect to water quality is missing,
and in such cases, decisions in respect to the use of water resources could be regarded as
an “informed” guess, with corresponding economic and social consequences, not only for
a specific locality, region or country, but in terms of international relations as well,
considering upstream - downstream users. The need for an informed decision-making
process is emphasized in Shultz (2003) as well.
2.2
Water quality - a random variable
River flow rates and water quality constituents are random probabilistic parameters,
which vary with time, therefore the analysis of a data set should include statistical time-
series tools. The information, which could be obtained from a data set, would depend
heavily on the statistical data analysis tools adopted. The basic statistical parameters,
which represent a water quality monitoring data set, are the mean and median values, the
variance and the standard deviation. All measurements with respect to a given parameter
could be fitted to a probability distribution. The most widely applied distribution is the
“normal” or Gaussian distribution, which is represented by a typical bell-shape curve. If a
data set complies with the normal probability distribution, the mean and median values
are identical, or close to each other. In asymmetrical data sets, characterized by high
standard deviation, the data set should be transformed to fit an asymmetrical probability
distribution curve. The coefficient of skewness is the statistical parameter, characterizing
the type of probability distribution of data sets. Values of this coefficient close to zero,
show a normal distribution. In analyzing water quality monitoring data, it could happen
often that the data sets are not distributed normally.
It is often necessary to find extreme values of a data set, which represent minimum or
maximum concentrations, characteristic for a data set. To do this, we should answer the
