WQI of Tiwari and Mishra
Uses and Limitation
The WQI of Tiwari and Mishra (1985) was not specific to groundwater but over the years it has been used extensively for groundwater-quality assessment, mainly in different regions of India, but outside as well (Ketata et al., 2011).
Categorization Table
Table 1. The WQI of Tiwari and Mishra rating and their categories
Standards Required
Any national or international water quality standards could be used in this method.
Variables Selection
This has been mostly done subjectively by different authors, choosing parameters which past experience had indicated to be of importance in their regions. For example, in areas where groundwater was known to be high in one or more elements such as boron and iodine, those elements were included
Calculation of WQI of Tiwari and Mishra:
This is calculated using the equations:
\begin{eqnarray*}
WQI = antilog\sum_{i=1}^{p} \ {W_{i}logq_{i}}
\end{eqnarray*}
where: wi is the weight and calculated as:
\begin{eqnarray*}
W_i =\frac{k}{Q_i}
\end{eqnarray*}
K is a constant and Oi corresponds to WHO (World Health Organization) or ICMR (Indian Council of Medical Research) standards of the parameters.
The quality rating Qi is given by:
\begin{eqnarray*}
Q_i =\frac{V_{actual}-V_{ideal}}{S_{standard}-V_{ideal}}*100
\end{eqnarray*}
where qi is the quality rating of the ith parameter for a total of n water samples, Vactual is the value of the water-quality parameter obtained from the laboratory analysis of the sample and Vstandard is the value of the water-quality parameter obtained from the water-quality standard. The value of Videal is 7 for pH and zero for all other parameters.
Case Studies based on Index
Case study 1.
Multivariate statistical technique and WQI were used to evaluate spatial variations in surface water quality of Mahi River Basin. Coupling of WQI with spatial interpolation technique has allowed categorizing the river into different pollution potential zones. In serious situation of water pollution, the management of water quality of the different river zones will be more and more important in planning the whole watershed and minimizing the environment losses. According to the sources of pollution, different measures should be adopted in order to control the total quantity of the pollutants and achieve the goal of sustainable use of the water resources. This study suggests that it is urgent to control point pollutions, all wastewater should be treated before discharge. It could be helpful to managers and government agencies in water quality management. Multivariate statistical methods like CA can be used to understand a complex nature of water quality issues and determine priorities to improve water quality depending on theWQI. The results indicate that most of the stations were influenced especially by industrial practices followed by agricultural and household wastewaters.
Case study 2.
Rameswaram, a holy island, is famous for the sacred Ramanathaswamy temple, which cements people of the country regardless of their place, residence, or their religion or creed. This coastal tract is experiencing a chronic fresh water shortage, despite a few spring sources. The study area is selected for the characterization of physico-chemical parameters viz., pH, EC, TDS, salinity, TA, TH, CH, MH, chloride, and fluoride for 150 groundwater samples and the impact of pre- and post-monsoons on the groundwater quality is studied. The water quality index advocates the transfer of groundwater quality from unacceptable status in the pre-monsoon into an acceptable status in the post-monsoon. The Langelier saturation index reflects the scaling tendency of groundwater in the study area. The Karl Pearson correlation matrix has approved the maximum influence of calcium and chloride on the total dissolved solids. It is interesting to conclude that the groundwater in the study area has very hard nature, especially of non-carbonate type.
References
Srivastava, P.K., Mukherjee, S., Gupta, M. et al. Characterizing Monsoonal Variation on Water Quality Index of River Mahi in India using Geographical Information System. Water Qual Expo Health 2, 193–203 (2011). https://doi.org/10.1007/s12403-011-0038-7