EVALUATION OF WATER QUALITY IN URBAN DELHI STRETCH OF RIVER YAMUNA USING STATISTICAL METHODS

Abstract

The present study deals with the variation of water quality characteristics over an urban stretch of the Yamuna River covering areas upstream, downstream and the entire length of the Delhi city. The study has been conducted over a period of six months. Water samples collected systematically from nine sites during October to February and examined for water quality evaluation through application of Regression analysis models. A regional perspective is provided with river water quality being interpreted in relation to catchment geography and to the observed point and non-point source inputs to the catchment. For many determinants, both diffuse and point sources appear to contribute to the riverine load in the study area. Point source inputs are important for phosphate, nitrate and micro-organic pollutants. Diffuse agricultural sources are particularly important in upstream arable areas, e.g. for nitrate, phosphate and micro-organics. In addition, widespread background geological sources contribute to loads of sulfate and phosphate. Sewage effluent is the most widespread and most significant point source of many pollutant chemicals in the study area. Low biochemical oxygen demand, nitrate, chloride and phosphate result from domestic effluent and commercial inputs, e.g. from sectors such as public places and fishery. Fish farms cause depletion in dissolved oxygen but on the whole, these changes were not observed to cause problems on a wider scale as of now. From the findings, a subset was selected for the water quality indices (WQI) analysis. Water quality of the Yamuna River at different points assessed by the WQI was compared. According to the quality indices during the study period, water quality in the study area of the river was average to good. To support and strengthen the findings, an analyses of the data based on multiple regression was done to examine whether seasonal or spatial variation in different parameters can be explained and predicted based upon their interrelationships in terms of source and mobility.