Water Pollution Index
Water Pollution Index – The construction of WQI requires first a normalization step, where each parameter is transformed into a 0-100% scale, with 100 representing the highest quality. The next step is to apply weighting factors that reflect the importance of each parameter as an indicator of the water quality (Boler, 1992; Conesa Fdez-Vitora, 1995; Estevan Bolea, 1989; Zagatto et al., 1998). The so constructed WQI gives a number that can be associated with a quality percentage, easy to understand for everyone, and based on scientific criteria for water quality.
Uses and Limitation:
The Water Pollution Index classification system adopted here is proposed by Jonnalagadda and Mhere (2001) and Dojlido et al. (1994). According to which, WQI in the range of 0–25 is very bad, 26–50 is bad, 51–70 is medium, 71–90 is good and 91–100 is excellent.
Categorization Table
Table 1 Water Quality Index Ranges for Different Classes of Beneficial Use
Standards Required for Water Pollution Index
No standard required for this index calculation.
Variables Selection
A total of 20 water quality parameters were considered for this index method as follows:
Table 1. List of considered 20 parameters
Calculation of Water Pollution Index:
The subjective water quality index, WQIsub, was calculated on the basis of the WQI proposed by Rodriguez de Bascaron (Conesa Fdez-Vitora V., 1995) as follows:
Where k is subjective constant. It represents the visual impression of river contamination (as could be evaluated by a person without training in environmental issues). It takes one of the following values according to the river condition:
- 00=water without apparent contamination (clear or with natural suspended solids).
- 75=light contaminated water (apparently), indicated by light non-natural color, foam, light turbidity due to no natural reasons.
- 50=contaminated water (apparently), indicated by non-natural color, light to moderate odor, high turbidity (no natural), suspended organic solids, etc.
- 25=highly contaminated water (apparently), indicated by blackish color, hard odor, visible fermentation, etc.
Ci is the value assigned to each parameter after normalization (Table 2).
Pi is the relative weight assigned to each parameter (Table 2). Pi value range from 1 to 4, with 4 representing a parameter that has the most importance for aquatic life preservation (e.g. dissolved oxygen), while a value of 1 means that such parameter has a smaller impact (e.g. chloride).
Case Studies based on Index
Case study 1
The use of WQI to evaluate spatial and seasonal changes in the water quality from the Suquia River in Cordoba City (Argentina) and nearby locations. The city urban activity produces a serious and negative effect on the water quality; this is particularly severe in locations following the city sewage discharge. The dry season shows the worst water quality.
Case study 2
An attempt has been made to assess the chemical water quality of the Danube River using water quality indices (WQIs). Water quality data sets of 11 chemical parameters along with two important physical variables obtained during 1 year in four sampling sites (collected at monthly intervals) were used. The Canadian Council of Ministers of the Environment Water Quality Index (CCME WQI) and the Bascaron Water Quality Index (BWQI) were selected to express the chemical quality of water for drinking water abstraction and general uses respectively, in addition, to provide information on the spatial variations along the river. The results of CCME-WQI revealed that the water quality was found “fair” in all sampling stations except one station, which was “marginal”. The outcomes of BWQI demonstrated that the water quality was “good” at all sampling stations. It was found that the CCME WQI has given more reasonable results and introduced representative outcomes of the raw data of the river.
References
Pesce, S. F., & Wunderlin, D. A. (2000). Use of water quality indices to verify the impact of Cordoba city (Argentina) on Suquýa river. Water Research, 34(11), 2915–2926.
Ismail, Alhassan, & Robescu Diana (2017). Chemical water quality assessment of the Danube River in the lower course using water quality indices. U.P.B. Sci. Bull., Series B, 79(4), 51-62.