Prediction of Surface Water Quality of Upper Ganga in Uttar Pradesh

Abstract

Abstract: With an increase in population and accelerated pace of industrialization, water quality is going to degrade day-by-day. The main source of water in India is from rivers. The Ganga River Basin is the world’s most populated and is home to half of India’s population, including two-thirds of the nation’s poor. This paper highlights the utility of statistical techniques for evaluating, interpreting complex data sets and recognizing spatial differences in water quality for effective management of river water quality. The Autoregressive Integrated Moving Average (ARIMA) model uses time-series data and statistical analysis to interpret the data and make future predictions. 6 water quality parameters Dissolved Oxygen, BOD, pH, Temperature, Electrical Conductivity and Total Coliform are analysed and predicted. In this work 4 monitoring station is taken for the prediction analysis and data is taken from the CPCB. In this work ARIMA model is giving the better prediction of temperature, total coliform and conductivity in compare of other water quality parameter pH, BOD and DO. The max value for correlation coefficient for Dissolved Oxygen, BOD, pH, Temperature, Electrical Conductivity and Total Coliform are respectively 0.73, 0.76, 0.79, 0.83, 0.84 and 0.85.