Water quality of the Chhoti Gandak River using principal component analysis, Ganga Plain, India

Bhardwaj, Vikram; Singh, Dhruv Sen; Singh, Abhay Kumar

doi:10.1007/s12040-010-0007-8

Cited by 76 publications

(31 citation statements)

References 16 publications

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“…Today, over 29 cities, 70 towns and thousands of villages extend along the Ganga banks. Nearly all of their sewage-over 1.3 billion liters per day-goes directly into the river, along with thousands of animal carcasses, mainly cattle (Bhardwaj et al 2010). Domestic and industrial wastewater constitute as a constant polluting source, whereas surface runoff is a seasonal phenomena mainly controlled by climate (Singh et al 2004).…”

Section: Introductionmentioning

confidence: 99%

Assessment of Ganga river ecosystem at Haridwar, Uttarakhand, India with reference to water quality indices

et al. 2014

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The river Ganges is regarded as one of the most holy and sacred rivers of the world from time immemorial. The evaluation of river water quality is a critical element in the assessment of water resources. The quality/potability of water that is consumed defines the base line of protection against many diseases and infections. The present study aimed to calculate Water Quality Index (WQI) by the analysis of sixteen physico-chemical parameters on the basis of River Ganga index of Ved Prakash, weighted arithmetic index and WQI by National sanitation foundation (NSF) to assess the suitability of water for drinking, irrigation purposes and other human uses. These three water quality indices have been used to assess variation in the quality of the River Ganga at monitored locations over an 11-year period. Application of three different indexes to assess the water quality over a period of 11 years shows minor variations in water quality. Index values as per River Ganga Index by Ved Prakash et al. from 2000 to 2010 ranged between medium to good, Index values as per NSF Index for years 2000-2010 indicate good water quality, while Index values as per the weighted arithmetic index method for the study period indicate poor water quality.

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Section: Introductionmentioning

confidence: 99%

Assessment of Ganga river ecosystem at Haridwar, Uttarakhand, India with reference to water quality indices

et al. 2014

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“…Resultados semelhantes aos obtidos nesse trabalho foram obtidos por Girão et al (2007) e por Bhardwaj et al (2010) As comunalidades permitem avaliar como o modelo descreve as variáveis originais; representam, pois, a correlação entre cada variável e os fatores extraídos, por isso, pode-se dizer que é uma medida da proporção da variância explicada pelos fatores extraídos. Dessa forma, verifica-se na Tabela 1 que duas variáveis explicadas pela primeira componente apresentaram valores de comunalidade superiores 0,83; duas variáveis selecionadas na segunda componente apresentaram comunalidade superior a 0,72; e uma variável explicada pela terceira componente apresentou comunalidade superior a 0,87, demonstrando que o modelo apresenta uma boa descrição dos dados originais.…”

Section: Resultsunclassified

Diagnóstico temporal e espacial da qualidade das águas superficiais do Córrego Bandeira, Campo Grande, MS

2015

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Resumo:A ocupação e o uso dos solos decorrentes de atividades humanas alteram sensivelmente os processos biológicos, físicos e químicos dos sistemas naturais. Essas alterações, quando ocorridas em uma bacia hidrográfica, podem ser avaliadas através do monitoramento da qualidade das águas superficiais. No presente trabalho, objetiva-se identificar os fatores determinantes da qualidade das águas superficiais da bacia hidrográfica do Córrego Bandeira, bem como agrupar os pontos de coleta quanto à similaridade das características físico-químicas selecionadas, para verificar o efeito da sazonalidade sobre a qualidade das águas estudadas, utilizando técnicas da estatística multivariada. Coletaram-se amostras de água superficial em seis pontos distribuídos ao longo do Córrego Bandeira, desde a nascente até a foz. As variáveis físico-químicas analisadas foram: coliformes termotolerantes, fósforo total, nitrogênio total, demanda bioquímica de oxigênio, sólidos totais, temperatura, turbidez, oxigênio dissolvido e pH. A análise de componentes principais permitiu a seleção de três componentes indicadores da qualidade das águas, explicando 75% da variância total. Todas as variáveis físico-químicas analisadas foram representativas da variabilidade da qualidade das águas superficiais do Córrego Bandeira. A análise de agrupamento formou dois grupos distintos de qualidade, que diferiram quanto aos valores das variáveis físico-químicas e quanto à sazonalidade. Palavras-chave: Agrupamento. Componentes Principais. Indicadores de Qualidade da Água. Abstract:The occupation and the use of land resulting from human activities can significantly alter the biological, physical and chemical processes of natural systems. Such changes taking place in a watershed can be evaluated by monitoring the quality of the surface water. The aim of this study was to identify the determining factors of surface water quality in the watershed of the Córrego Bandeira River, and to group collection points by similarity of the selected physical and chemical characteristics, so as to verify the effect of seasonality on the quality of the waters under study using techniques of multivariate statistics. Samples of surface water were collected from six points along the Córrego Bandeira River, from its source to the mouth. The physical and chemical variables to be analysed were: thermotolerant coliforms, total phosphorus, total nitrogen, biochemical oxygen demand, total solids, temperature, turbidity, dissolved oxygen and pH. Principal component analysis made possible the selection of three components as indicators of water quality, explaining 75% of the total variance. All of the physical and chemical variables analysed were representative of the variability in surface water quality of the Córrego Bandeira River. Cluster analysis however formed two distinct groupings by quality, which showed different values for the physical and chemical variables, and differed in seasonality.

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“…While, third group consists of association between three subgroups; in which association found between K + , HCO 3 , Mg +2 with Cl, SAR, Na + , pH, Ca +2 , Cu all with Zn. These ions suggest the associated with a combination of various hydrogeochemical processes and augment more mineralized water [24].…”

Section: Sites and Variables Similaritymentioning

confidence: 93%

Multivariate statistical characterization of water quality analysis for Erbil wastewater channel

Shekha

2013

IOSR-JESTFT

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Water quality of the Chhoti Gandak River using principal component analysis, Ganga Plain, India

Cited by 76 publications

References 16 publications

Assessment of Ganga river ecosystem at Haridwar, Uttarakhand, India with reference to water quality indices

Assessment of Ganga river ecosystem at Haridwar, Uttarakhand, India with reference to water quality indices

Diagnóstico temporal e espacial da qualidade das águas superficiais do Córrego Bandeira, Campo Grande, MS

Multivariate statistical characterization of water quality analysis for Erbil wastewater channel

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