ASSESSMENT OF ENVIRONMENTAL QUALITY OF RIVER GANGA CATCHMENT AREA USING MODELLING TOOLS

Abstract

River Ganga which originates from Gaumukh and travels through Gangotri Glacier, Devprayag, Rudraprayag, Haridwar, Prayagraj, Varanasi, Patna, Rajmahal, Howrah and finally meet the Bay of Bengal accounts for 26% of India’s drainage area with its stretch of 8,62,769 Km2. The self-purification capacity of River Ganga is stressed out due to industrialisation and river lost its ability to digest organic waste by its own. The data for the research was collected from CPCB ENVIS and interpolation tool of ARCGIS software and statistical tools of MINITAB is used for water quality and air quality of River Ganga and nearby areas. The BOD value varies from 0 to 6 mg/L in the entire region except at Kanpur region. The BOD varies from 6 mg/L to 80 mg/L at Kanpur region in 2016. The DO value varies from 4 to 6 mg/L in the state of West Bengal which tells that the water quality of River Ganga in West Bengal is slightly polluted to moderately polluted in terms of dissolved oxygen present in it. The water quality of West Bengal stretch and between Prayagraj and Mirzapur has medium quality of water and WQI ranges from 50 to 70. The air quality near River Ganga in Uttar Pradesh and remaining part of Bihar is poor with AQI score in the range of 201-300 due to industrial emission and stubble burning. At temperature 18˚C, DO available is 9 mg/L and DO present at 27˚C is 7.5 mg/L. The pH, EC, Temperature, Nitrate-N, BOD, TC, FC, WQI, SO2, NO2, PM10 and AQI doesn’t follow the normal distribution based on Anderson Darling Normality test while DO and PM2.5 follow the normal distribution. It can be concluded based on the study that the environmental pollution near River Ganga may falls in moderately polluted area and some remedial action be able to lead to good quality of air as well as water. With the emergence of the effort of NGRBA it can be concluded that the water quality of River Ganga improves day by day from 2007 to 2016. The ANN model developed can be improved by providing better training dataset.