Prati’s Index
Prati’s Index -The need to determine the chemical, physical and biological characteristics of natural water resources is essential in view of their utilization particularly as a source of municipal water supply. The increased demand for water (WHO, 1966), as a consequence of population growth, agricultural and industrial development, has been accompanied almost everywhere by research oriented towards the definition of criteria and guides for surface water quality. In many countries the need for control of pollution has resulted in legislation and regulations (WHO, 1967) which have, however, been based on different criteria and different systems of classification as regards quality (LITWIN, 1965). Two main approaches seem m general to have been used. The first is based on the characteristics of effluents before their discharge into rivers; thus, by requiring a certain degree of treatment, both the enforcement regulations and the selection of type of treatment have been relatively simplified. The second approach, based on the quality to be maintained in rivers after dilution of effluents and thus taking into account the natural capacity of rivers for dispersion and self-purification, makes it more difficult to decide on the discharge of waste waters, particularly where several types of effluent are present in the same part of a river (MCKEE and WOLF, 1963).
In this last case, certain considerations by Kerri (1966, 1967) seem especially pertinent. On the basis of experience in the Ruhr river basin, he advocates discharge of effluents from treatment plants that are so designed as to fully utilize the dilution and self-purification capacity of rivers. The author suggests also an economic model facilitating the sharing of treatment costs, proportionately, among the various users according to their “polluting” capacity.
In the classification of river water quality, there are two main considerations, i.e. the use of the water and the concentrations of the pollutants discharged. The various classes are in any case determined by the concentrations, after dilution, of selected pollutants (or indices of pollution) according to a scale of proportion for the various levels of pollution. The application of this procedure, however, implies that the same polluting capacity is assumed for various pollutants (or selected indices) within a certain class, and no consideration is given to the cumulative polluting capacity of the various pollutants selected.
This note is a preliminary contribution towards the identification of an “implicit index of pollution” based on river water quality classification.
We have thus been looking for an index as a numerical expression of the degree of pollution, and which takes into account the various pollutants present at the same time (though measured separately). This index, increasing with the degree of pollution, could be used for the numerical evaluation of a purely qualitative characteristic expressed by the term “pollution”.
Our objective has therefore been to determine as many mathematical expressions as there are pollutants, to transform concentrations into levels of pollution expressed in new units which would then be the “units of measurement of pollution”.
These mathematical expressions are so constructed for each polluting factor, that their numerical value is no longer proportional to the concentration but to the “polluting effect” relative to other factors. In this way, although one pollutant may be present in smaller concentrations than another, it will have a larger number if its polluting effect is greater for example, on the basis of the standard values arbitrarily selected in TABLE l, in water containing l ppm of iron and l0 ppm of COD, the numerical value–representing polluting capacity–will be higher for iron than for COD (4-27 > l.).
It is obvious that the choice of the new unit of pollution is an arbitrary one since the evaluation of pollution is a relative proposition. However, it will have to represent coherently, as mentioned above, the relationship of the polluting capacity of the various contaminants selected. On this assumption, any pollutant or conventional index of pollution can be taken as a basis for reference and its scale (expressed as concentrations) used accordingly in a classification system, to arrive at the new numerical values as a measure of pollution.
It will be noted that no transformation through a mathematical expression will be needed for the polluting factor selected as referee. In fact, in the two classifications (the conventional and the new one), the values will remain the same, but for the difference that, while m the conventional classification these are expressed in concentrations (ppm, m 1-1 or other), in the new one they will be expressed as dimensionless numbers.
We then proceeded to transform the scales of concentrations of other pollutants (or parameters), according to the concept described above and taking into account their various polluting capacities, into new units related to the selected basic referee factor. The new proposed “unit of measure of pollution” can be assumed to be the arithmetic mean of the new values found for each pollutant or parameter.
Uses and Limitation:
In this preliminary note we have kept in mind the application of Prati’s Index method to the evaluation of surface water quality in Ferrara, Italy, particularly with a view to establishing an inventory of the quality of water resources in a region or country. It is obvious that for this purpose objective and comparable criteria have to be used.
Although Prati’s Index method lacks somewhat in objectivity, we think it may serve a useful purpose in securing comparability as regards the degree of pollution present in rivers in various countries.
Categorization Table
Standards Required
None water quality standards is required for the calculation of this method (Prati’s Index).
Variables Selection
The water quality parameters viz. pH, DO, BOD, TSS, Permanganate, Cl, Ammonia, NO3, Fe, Mg, Alkyl Benzene Sulphonates and Carbon chloroform exact are considered as the significant indicator parameters of surface water quality in this index method.
Calculation of Prati’s Index:
The Prati’s Index was computed as the arithmetic mean of the 13 sub-indices:
\begin{eqnarray*}
I =\frac{1}{n} \sum_{i=1}^{n} \ {I_{i}}
\end{eqnarray*}
where Ii is the sub-index function for ith parameter. i = 1, 2, . . ., n and n = number of parameters which is 13 in this index method.
Table 1. Mathematical expression for sub-index function

Case Studies based on Prati’s Index
Ioanna et al. (2018) attempts to examine the comparative performance of seven different WQIs, as they were computed for Polyphytos Reservoir‐Aliakmon River in Greece, based on water quality monitoring data for the period between June 2004 and May 2005. The WQIs applied were: Prati’s Index of Pollution, Bhargava’s Index, Oregon WQI, Dinius’ Index, CCME WQI, NSF WQI and the Weighted Arithmetic WQI. Significant discrepancies were observed in classification results between the different methodologies. Among others, it was concluded that NSF and Bhargava indices classify the reservoir in higher quality classes, Prati’s and Dinius indices in medium, while CCME and Oregon in lower quality categories.
References
Ioanna Zotou, Vassilios A. Tsihrintzis and Georgios D. Gikas (2018). Comparative Assessment of Various Water Quality Indices (WQIs) in Polyphytos Reservoir‐Aliakmon River, Greece. Proceedings, 2, 611; doi:10.3390/proceedings2110611