LONG-TERM ASSESSMENT OF GOMTI RIVER WATER QUALITY AT SULTANPUR, INDIA: A MULTIDIMENSIONALAPPROACH

Abstract

The Gomti River, a prominent groundwater-fed river in Uttar Pradesh, India, faces significant pollution pressures from industrial effluents and domestic wastewater. This study presents a comprehensive analysis of the Gomti River's water quality at Sultanpur over 20 years (1998- 2017), employing Water Quality Indices (WQIs) and multivariate statistical techniques to evaluate pollution levels and identify key factors influencing water quality. The water quality was assessed using four WQIs: Comprehensive Pollution Index (CPI), Synthetic Pollution Index (SPI), Nemerow's Pollution Index (NPI), and Arithmetic Water Quality Index (AWQI). Descriptive statistics were calculated for key physico-chemical parameters such as Dissolved Oxygen (DO), pH, Electrical Conductivity (EC), Total Dissolved Solids (TDS), Biochemical Oxygen Demand (BOD), Total Hardness (TH), and major ions and nutrients (e.g., Sodium, Potassium, Calcium, Magnesium, Nitrate, Total Phosphorus, Chloride, Sulphate, Ammonia, Fluoride, Boron). Principal Component Analysis (PCA) and Cluster Analysis (CA) were used to identify major pollution sources and temporal variations. The study found that the mean values for DO, pH, EC, TDS, and BOD were 6.92 ± 1.18 mg/L, 8.39 ± 0.35, 388.49 ± 109.75 µS/cm, 312.87 ± 102.62 mg/L, and 2.65 ± 0.74 mg/L, respectively. DO levels fluctuated between 3.0 mg/L and 11.8 mg/L, indicating varying oxygen availability for aquatic life. The pH ranged from 7.6 to 9.2, reflecting slightly alkaline conditions. EC and TDS values exceeded recommended limits at certain times, highlighting potential sources of pollution from agricultural runoff and industrial discharges. BOD values indicated moderate organic pollution (2.65 mg/L), with occasional peaks suggesting episodic pollution events. PCA revealed that the key parameters derived through principal components affecting the water quality indices throughout the study were Total Hardness (TH), Total Dissolved Solids (TDS), Magnesium (Mg2+), Total Alkalinity (TA), Chloride (Cl- ), Potassium (K+ ), Sodium (Na+ ), pH, Dissolved iv Oxygen (DO), Fluoride (F- ), Sulphate (SO4 2- ), and Boron (B) with a total cumulative variance of 62.39% in the dataset. Over the past two decades, a comprehensive water quality assessment indicates an improvement. The analysis of water quality indices provides a comprehensive overview of the pollution status. The Comprehensive Pollution Index (CPI) findings suggest that the water quality was categorized as Slightly Polluted (0.41-1.00) 90% of the time, while the remaining 10% fell within the Sub-Clean range (0.21-0.40). According to the Synthetic Pollution Index (SPI), water quality was classified as Slightly Polluted (0.21-0.40) in 45% of observations and as Suitable for Drinking (≤0.20) in 55% of cases. Nemerow's Pollution Index (NPI) revealed that water quality was Lightly Polluted (1-2) in 18% of the samples, whereas 82% were categorized as Not Polluted (≤1). The Arithmetic Water Quality Index (AWQI) showed that 78% of the water samples were rated as Poor (51-75), 18% as Very Poor (76-100), and only 4% as Good (26-50). Regression analysis revealed significant correlations between PCA-derived parameters and the original CPI-based WQI, with R² value (0.83) indicating strong predictive power for water quality assessment. The study also identified seasonal variations in water quality, with higher pollution levels during the dry season due to reduced dilution and increased pollutant concentration. The findings emphasize the need for continuous monitoring and effective management strategies to mitigate pollution and improve the Gomti River's water quality. Implementing comprehensive governance frameworks and advanced analytical techniques can lead to significant improvements, benefiting both the ecosystem and the local population. This study contributes valuable insights for policymakers and stakeholders in understanding sustainable water management practices and ensuring the long term health of river ecosystems.