Integrated PCA–RNN approach for surface water quality assessment in the Mahanadi river system

Singh, R. B.; Patra, K. C.

doi:10.1007/s13762-024-05496-w

Cited by 4 publications

(1 citation statement)

References 55 publications

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“…The Pearson correlation matrix given in Table5provides insights into the relationships between different water quality parameters measured in the study(Singh and Patra 2024). From the table it can be seen that TDS has positive correlation with EC (0.81), chloride (0.52), nitrate (0.44), sulphate (0.44), total hardness (0.44), total alkalinity (0.52), carbonate (0.53) and bicarbonate (0.53).…”

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confidence: 99%

Integrated Geochemical Analysis of Groundwater Quality and Human Health Risks by Using Multivariate Statistical Methods: A Case Study of Mayurbhanj District, Odisha, India

Sahoo,

Panda,

Swain

et al. 2024

Preprint

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Mayurbhanj district is predominantly inhabited by tribal communities. Among the various tribal groups in Odisha, Mayurbhanj alone accommodates 45 distinct categories. These tribal communities primarily rely on natural water sources such as rivers, streams, and tube wells for drinking purposes without undergoing additional purification processes. Hence, investigating the factors affecting groundwater quality is essential to ensure its safety for drinking purposes and mitigate the health risks associated with the consumption of contaminated water. In the present study, groundwater quality of 145 water samples from different sources of Mayurbhanj district was analysed. The geographical coordinates of sample locations and measurements of groundwater quality parameters were used in Geographic Information System software, ArcGIS pro, to construct the spatial distribution and spatial variation maps. Five significant principal components having eigen value greater than 1 with total variance of 73.43. Kaiser-Meyer-Olkin (KMO) test was above 0.5 which shows that data collected from the study area are accurate for analysis. Electrical conductivity, F−, pH and NO3− varies in the range of 42 to 1754 µS/cm, 0.01 to 1.97 mg/l, 5.5 to 7.9 and 0.1 to 21.2 mg/l respectively. The non-carcinogenic health risk assessment indicates that the hazard quotient (HQ) values attributed to fluoride ion and nitrate ion exposure range from 0.43 to 0.46 for children and 0.23 to 0.26 for adults, and from 0.002 to 0.6 for children and 0.001 to 0.3 for adults, respectively. The children are comparatively at slightly more prone to health risk in comparison to adults. Gibbs diagram shows that most of the water samples comes in the region of rock-water interaction dominance in Gibbs plot of TDS vs chloride ion concentration. In the loading biplot for the study area, the first principal component in the horizontal axes has positive coefficients for carbonate, chloride, bicarbonate, total alkalinity, calcium hardness, magnesium hardness, total dissolved solids, electrical conductivity, fluoride. TDS has positive correlation with EC (0.98), chloride (0.525), nitrate (0.445), sulphate (0.445), total hardness (0.438), total alkalinity (0.524), carbonate (0.528) and bicarbonate (0.535). The software used for statistical study are, Minitab, Origin and SPSS. The results of this study would be useful for the Government and policy makers to provide safe and quality drinking water to the tribal community.

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confidence: 99%

Integrated Geochemical Analysis of Groundwater Quality and Human Health Risks by Using Multivariate Statistical Methods: A Case Study of Mayurbhanj District, Odisha, India

Sahoo,

Panda,

Swain

et al. 2024

Preprint

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GHPSO-ATLSTM: a novel attention-based genetic LSTM to predict water quality indicators

Singh,

Patra,

Samantra

2024

Stoch Environ Res Risk Assess

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A Comparative Assessment and its Characterization of the Integrated Novel Water Pollution Index and its Statistical Approach for the Evaluation of Spatial Variations Using Factor Analysis: A Geospatial Approach in Mahanadi River, Odisha

Das

2024

MATEC Web Conf.

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Knowledge on water quality and its assessment, is necessary for both human health and environmental benefit. To account for spatial distribution, surface water quality parameters were analysed using integrated interpolation, geographical information systems (GIS) and multivariate analysis. A total of 19 locations and 13 water quality indicators were analysed, for a duration of six years (2018-2024). The study’s main objective was to assess the seasonal and regional variations in the water quality index (WQI) of Mahanadi River in Odisha using (N) pi, (S) pi, (O) pi, (C) pi, (E)y-WQI, Int w-WQI and Multivariate Statistical tools namely Factor Analysis (Fa). However, in the current investigation, pH, HCO3-, Na+, K+ and Mg2+ were within the permissible limits as per WHO standards. According to this study, the order of prevalence of ion concentrations is signified as follows: Mg2+ > Ca2+ > K+ > Na+ for cations and HCO3- > Cl- > SO42- for anions. The analysis of (N) pi indicated that about 15.79% of the sampled area, is affected by turbidity content, which is highly unsuitable for consumption. However, the remaining area (84.21%) is within the safe category of water. Classification of water based on (S) pi represents most of water samples falls between good water quality. Three unsuitable samples is noted as a result of excessive TDS and EC. In case of (O)pi, over 84.21% of the samples fell into categories of excellent, indicating the suitability for human activities. Using surface water quality results from (C) pi model, that reflects that out of 19 samples, 16 were suitable for drinking. Whereas 2 were polluted and 1 is seriously polluted, thus promotes unsuitability. Although there are several established techniques for calculating the WQI, the current study uses the quality index to consider a variety of water quality concerns in a cohesive manner. Meanwhile, in case of (E)y-WQI, 84.30% were excellent whereas 10% and 5% were poor and high polluted category. Over 42.11% of the samples fell into the categories of poor/very poor/not suitable, using the Int w-WQI diagram. Therefore, using these six approaches resembles a precise and comprehensive method to comprehend water quality in relation to pollution for human usage. In later stage, a factor analysis (Fa) can be applied to lessen the subjectivity and dimension of water quality characteristics. It reveals that the first five principal components explain almost 95.61% of dataset variation. This method removes the aggregation problems, weighting, opacity, and biases seen in traditional water quality evaluation techniques. The results of Fa suggested that turbidity, TKN, Ca2+ and Cl-, were the primary determinants of the water’s quality. The amount of organic pollution that was released into the river was influenced by anthropogenic activity in the vicinity of the river. In addition, the traditional dense habitation next to the river and the manufacturing waste that is transported from upstream to downstream are the sources of the high amount of TKN in urine and faeces. Therefore, given the high spatial distribution of geogenic turbidity and TKN occurrence, the study’s findings minimize uncertain causes and offer insights into surface water pollution regimes. They will also be useful to policy makers in helping to better plan, allocate resources, and manage the area’s potable water supply.

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Integrated PCA–RNN approach for surface water quality assessment in the Mahanadi river system

Cited by 4 publications

References 55 publications

Integrated Geochemical Analysis of Groundwater Quality and Human Health Risks by Using Multivariate Statistical Methods: A Case Study of Mayurbhanj District, Odisha, India

Integrated Geochemical Analysis of Groundwater Quality and Human Health Risks by Using Multivariate Statistical Methods: A Case Study of Mayurbhanj District, Odisha, India

GHPSO-ATLSTM: a novel attention-based genetic LSTM to predict water quality indicators

A Comparative Assessment and its Characterization of the Integrated Novel Water Pollution Index and its Statistical Approach for the Evaluation of Spatial Variations Using Factor Analysis: A Geospatial Approach in Mahanadi River, Odisha

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