Large cities face water quality and quantity problems due to increasing population and improper disposal of solid and liquid wastes. It is essential to monitor the water quality to take corrective measures. This study was carried out in one of the densely populated metropolitan cities in India to ascertain the suitability of groundwater for drinking and irrigation activity, identify the processes controlling the geochemistry of groundwater and the impact of Adyar River on the groundwater quality. Magnesium and pH concentration in groundwater of this area were within the maximum permissible limits of WHO standards. Sodium and potassium concentration of groundwater were greater than the permissible limit in 30.8 % and in 50 % of the samples, respectively. About 35 % of the groundwater samples were not permissible for drinking based on the electrical conductivity (EC). The EC of groundwater was increasing towards the coast. In general, the quality of groundwater for irrigation purpose vary from moderate to good based on Na%, magnesium hazard, residual sodium carbonate, sodium absorption ratio, permeability index, and USDA classification. Na-Cl and Ca-Mg-Cl were the dominant groundwater and surface water type. Increased ionic concentration of groundwater towards the eastern part of the study area is due to the discharge of industrial effluents and domestic sewage into the Adyar River. Seawater intrusion is also one of the reasons for Na-Cl dominant groundwater near the coast. Evaporation and ion exchange were the major processes controlling groundwater chemistry in this area. The groundwater quality of this region is affected by the contaminated surface water.
Muttukadu Backwater, located on the east coast of Tamilnadu, is one of healthiest estuarine environments in the region. A study pertaining to seasonal variations in physico-chemical properties in water was conducted at nine sites of Muttukadu Backwater for a period of one year (January to December 2009). Multivariate statistical techniques, such as cluster analysis and principal component analysis (PCA), were applied to evaluate the variation in water quality of Muttukadu Backwater and to identify pollution sources. In order to analyze water quality, a geographic information systems (GIS) software package, Arc GIS version 9.3, was used (Esri, Redlands, California). An interpolation technique, inverse distance weighting, was used to produce the spatial distribution of water quality parameters over the backwater. The purpose of the technique was to aid in protection of the environment and ecology of the estuary and aid in effective management. In the present study, observed values of salinity, nitrite, nitrate, ammonia, total nitrogen, phosphate, and silicate were significantly high in the estuarine zone. PCA resulted in three factors explaining 75.9% of the total variance. Principal component 1 exhibited a high correlation with significant physico-chemical variables representing the influence of tidal action and sandbar formation. Principal component 2 represented natural pollution as a result of surface runoff. Principal component 3 represented natural pollution as a result of nutrient pollution.
Summary
In this paper, the Guideline Value (GV) of land is automatically generated via a utilitarian model, which consists of a multilevel regression predictor and an association rule. The utilitarian model generates GV for the Chennai area land in Tamil Nadu, India. In the existing system, the land GV is fixed based on the market price. The GV is revised according to market analysis, every 2 years, and creates an anomaly in price, causing loss to the government of Tamil Nadu. In the utilitarian GV pricing model, with the survey number or the street name entered in the website, the GV generates automatically. The automatic generation of the GV in the website is based on the real‐time calculation of the distance between the spatial and environmental parameters and the type of land use collected through a geographical information system. From the result, the utilitarian model provides 85% accuracy in the automated GV generation of land. The accuracy is evaluated through the Buyer Acceptance Testing (BAT) for the present and utilitarian guideline value.
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