Regression Models For Prediction Of Water Quality In Krishna River

Abstract

The River Krishna and its tributaries drain three important states of South India. The river water plays a very important role in the overall socioeconomic development of Andhra Pradesh.  In large river basins monitoring non-point sources pollution is rather difficult and expensive and is subjected to analytical errors. Hence, modeling water quality using land use data of the basin is attempted in the present study. The contribution from non-point sources (runoff from the river basin) is quiet considerable as the river drains various type of land uses. In this context, it is necessary to make a detailed study of the water quality of the river, to estimate the level of pollution and also main sources of pollution. Correlation studies explain the relationships, between dissolved solids concentration and land use of the basins. The multiple regression models accounted for significant variation in concentrations for majority of dissolved solids. The predicted concentrations are in good agreement with the observed values. The proposed models can be useful for planning land use controls in integrated water quality management program. As water quality of flowing water is closely linked to the land use in the basin, it is essential to include land use management in future river basin planning. Carefully designed land use studies to identify characterized and quantity of non point sources is essential elements to be emphasized to plan water quality management programme. The results of study indicate relative importance of non point sources pollution in addition to point sources pollution.

Keywords: Dissolved solids, Land use planning , Regression models, Water quality.