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A B S T R A C TThe present study intended to calculate water quality indices (WQIs) for six different areas of Batlagundu, Dindigul District in order to ascertain the quality of water for public consumption and other domestic purposes. This paper deals with the study on the influence of environmental parameters on the water quality. In this study, five WQIs have been determined on the basis of 24 physico-chemical parameters. The parameters, namely, temperature, pH, sulphate, potassium, nitrate, phosphate, DO, BOD and COD were within the permissible limits of BIS and WHO while other parameters such as turbidity, total dissolved solids, electrical conductivity, total hardness, total alkalinity, calcium, magnesium, chloride, nitrite, fluoride, sodium and iron were found to exceed the limit. Results of WQIs indicated that the quality of water was deteriorated by natural and anthropogenic sources. The aforesaid study showed that the groundwater of the above-selected sampling sites was not safe for human consumption but could be used for domestic purpose after purification.

Water quality assessment is essential to ensure viable safe use of the resources for drinking, agricultural and industrial purposes. Deterioration of groundwater quality due to anthropogenic activities is increasing at an alarming rate in most parts of Dindigul district, but limited work has been carried out on groundwater quality and monitoring. This paper highlights the groundwater quality and compares its suitability for drinking and irrigation purpose of Batlagundu block in Dindigul district of Tamil Nadu. Eighteen groundwater samples were collected systematically in triplicates during the year 2013-2014. The physical and chemical parameters of the analytical results of groundwater were compared with the standard guideline values recommended by the Bureau of Indian Standards and World Health Organization for irrigational suitability, domestic usage. Further hydrogeochemical data have been plotted in standard graphs such as Piper trilinear diagram, US Salinity Laboratory (USSL), Giggenbach triangle diagram and Schoeller diagram. The mathematical models are used to estimate water quality parameters and to describe realistic water situations. It is proved that electrical conductance is an important water quality parameter. Hydrofacies diagram reported that alkaline earths (Ca 2+ and Mg 2+) significantly exceed the alkalis (Na + and K +), while acids of (Cl − and HCO 3 −) exceed the acids of (SO 4 2− and CO 3 2−). Therefore, the chemical compositions of the study area were characterized by the Ca-Mg-HCO 3 water type and Na-Cl type. USSL diagram of the study area revealed that most of the sampling sites possess high salinity and low-to-medium sodium hazard indicated that water samples are poorly suitable for usual agropurposes. Giggenbach triangular diagram indicated that the samples have not gained equilibrium with their host rocks, presumably due to fact circulation of fluid through the rock features. The present research work thus concludes that groundwater in the study area is chemically unsuitable for domestic and agricultural uses. It is recommended to carry out a continuous water quality monitoring program and development of effective management practices for utilization of water resources.

The objective of this work is to study the physico-chemical properties of riverbed sand collected from mullai periyar river basin near Gudalur in Theni district, Tamilnadu, India. In order to understand the adsorption property of sand, pH, pH zero point charge (pHzpc), cation exchange capacity (CEC), Bulkdensity and surface area were measured. The cation exchange capacity (CEC) of riverbed sand was estimated using the copper bis-ethylenediamine complex method. The specific surface area and CEC of soil were 15.25 m 2 g-1 and 43.5 meq g-1 respectively. The result revealed that riverbed sand can acts as good adsorbent for removal of heavy metal ions from aqueous solution and wastewater.

A three layer feed forward artificial neural network (ANN) with back propagation training algorithm was developed to model the adsorption process of Cr(vi) in aqueous solution using riverbed sand containing quartz/feldspar/wollastonite (QFW) as adsorbent.