A model-based prediction and analysis of seasonal and tidal influence on pollutants distribution from city outfalls of river Ganges in West Bengal, India and its mapping using GIS tool

Abstract

River Ganges (locally called as river Ganga) is one of the most scared rivers in India. The river is symbol of hope, faith and is worshipped for its wholesomeness due to its purity and sanctity. Pollution of river water due to anthropogenic activity is a very common issue worldwide. Similarly, river Ganga pollution in India throughout its entire courses, is a major concern due to city outfalls. This river, also named as river Hooghly in West Bengal, India, is exposed to outfalls carrying domestic wastewater of its both bank and their distribution in river Ganga is strongly influenced by season and tide. This study aimed to generate an idea of distance and direction wise changes of concentration of pollutants in wastewater in river Ganga. During 2014, the selection of five major outfalls was done by considering Dissolved Oxygen (DO), Biochemical Oxygen Demand (BOD), heavy metals, total fecal coliform level, and the study continued for next four consecutive years to find out the influence of tide and season. Geographical Information System (GIS) based maps provided a better reflection of these changes. Student’s t-test highlighted the significant changes in concentration of parameters season wise. A significant higher value of DO, BOD, nitrate nitrogen, and chloride were found in pre-monsoon season compared to monsoon season. Regression Equation generated for highly correlated parameters (coliform and heavy metals) helped to predict the level of one parameter with others. The zone of influence of BOD, DO, phosphorus and nitrate nitrogen from each of the five selected outfalls was very prominent. Acoustic Doppler current profiler at two of the five outfalls helped to estimate strip-wise depth average discharge which helped to estimate the value of water quality parameters by Plug Flow Model during high tide and low tide. A strong tidal variation was observed during low tide. This study helped to predict the influential zone from outfalls which will help to generate an alternative solution of river water use. This approach can be applied globally to prepare river water usage guidelines.

Seasonal and Tidal Influence on Surface Water Quality – A Case Study in the Hau River Segment, Vietnamese Mekong Delta Province

“…Meanwhile, at low tide, the DO concentration did not differ significantly between the sampling stations, ranging from 4.63±0.37 to 4.68±0.36 mg/L. The DO concentration measured at two times of low tide showed the presence of organic waste in the study area, leading to the rapid growth of microorganisms that consumed dissolved oxygen, thereby reducing DO in water (Kamarudzaman et al, 2019, Kar et al, 2022. The average biochemical oxygen demand in a year is not much different between the two tidal currents (Figure 2D).…”

“…The difference in discharge and flow rate between high tide and low tide leads to a difference in river water quality between the two tidal streams. During low tide, the discharge and flow rate in the river are poor, so the pollutant concentration increases and vice versa (Kamarudzaman et al, 2019, Cereja et al, 2022, Kar et al, 2022. In addition, the tidal regime also aff ects the movement of pollutants and the dispersion of pollutants from diff erent discharge points (Kar et al, 2022).…”

“…During low tide, the discharge and flow rate in the river are poor, so the pollutant concentration increases and vice versa (Kamarudzaman et al, 2019, Cereja et al, 2022, Kar et al, 2022. In addition, the tidal regime also aff ects the movement of pollutants and the dispersion of pollutants from diff erent discharge points (Kar et al, 2022). Fatema et al (2015) suggested that tidal activity has changed the temperature, salinity, pH, dissolved oxygen, nitrogen and phosphate in the river water environment.…”

Evaluating Surface Water Quality in a Coastal Province of Vietnamese Mekong Delta Using Water Quality Index and Statistical Methods

“…Fig. 4 showed that the DO concentration at the time of the study was relatively low (less than 4 mg/L compared with QCVN) [22] indicating the occurrence of easily biodegradable organic matters in the water bodies. The average biochemical oxygen demand over the three monitoring times was also recorded to be low and there was no statistically significant difference between seasons (p>0.05).…”

“…DO had a moderate to high negative correlation with parameters of BOD (r = -0.308), COD (r = -0.414), TOC (r = -0.529) and parameters N-NH 4 + , N-NO 2 -, P-PO 4 3-, TN, TP, Fe, coliform were weak. It showed that when the concentration of organic substances and nutrients in the water is high, the demand for oxygen increases, causing the DO concentration in the water to decrease [22]. EC conductivity had a moderate to high positive correlation with TSS (r = 0.508) and Cl -(r = 0.994) parameters.…”