Water quality modelling of the river Yamuna (India) using QUAL2E-UNCAS

Paliwal, R. K.; Sharma, Prateek; Kansal, Arun

doi:10.1016/j.jenvman.2006.02.003

Cited by 106 publications

(74 citation statements)

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“…Throughout the year, the river flows like an open sewer d/s Wazirabad barrage and there is no aquatic life in this stretch. The main reasons for the poor river quality are addition of huge quantity of wastewater generated from the city and no fresh water flow in the river, as also studied by few water quality modeling studies (Paliwal et al 2007;Sharma and Singh 2009). Only 67% of the total sewage treatment capacity is being utilized in the capital city.…”

Section: Discussionmentioning

confidence: 99%

Water quality analysis of River Yamuna using water quality index in the national capital territory, India (2000–2009)

2011

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River Yamuna, in the national capital territory (NCT), commonly called Delhi (India), has been subjected to immense degradation and pollution due to the huge amount of domestic wastewater entering the river. Despite the persistent efforts in the form of the Yamuna Action Plan phase I and II (YAP) (since 1993 to date), the river quality in NCT has not improved. The restoration of river water quality has been a major challenge to the environmental managers. In the present paper, water quality index (WQI) was estimated for the River Yamuna within the NCT to study the aftereffects of the projects implemented during YAP I and II. The study was directed toward the use of WQI to describe the level of pollution in the river for a period of 10 years (2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009). The study also identifies the critical pollutants affecting the river water quality during its course through the city. The indices have been computed for pre-monsoon, monsoon and post-monsoon season at four locations, namely Palla, ODRB, Nizamuddin and Okhla in the river. It was found that the water quality ranged from good to marginal category at Palla and fell under poor category at all other locations. BOD, DO, total and fecal coliforms and free ammonia were found to be critical parameters for the stretch.

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Section: Discussionmentioning

confidence: 99%

Water quality analysis of River Yamuna using water quality index in the national capital territory, India (2000–2009)

2011

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“…A SMC é utilizada para simular sistemas complexos constituídos de variáveis aleatórias (PALIWAL et al, 2007). Neste estudo, as variáveis aleatórias são os dados de entrada, os quais são gerados aleatoriamente segundo uma distribuição uniforme e dentro de uma faixa pré-especificada (Tabela 3).…”

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“…A estimativa dos valores da porcentagem de variação foi baseada nos trabalhos realizados por Paliwal et al (2007) e Costa & Teixeira (2011). O elevado valor para K 2 (50%) deve-se à imprecisão das estimativas realizadas pelas equações empíricas (MELCHING & FLORES, 1999;HAIDER et al, 2013).…”

Section: Este Estudo Trata Das Incertezas Associadas Aos Dados De Entunclassified

“…Neste estudo, apenas a reaeração atmosférica e a degradação da matéria orgânica carbonácea foram consideradas no balanço de OD (Equação 2). Essas simplificações são comuns quando a modelagem é realizada em rios com elevada carga poluidora, em que a turbidez elevada e a baixa concentração de OD no corpo de água reduzem o efeito da fotossíntese/respiração e da nitrificação, respectivamente (DROLC & KONCAN, 1996;PALIWAL et al, 2007).…”

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Análise de incerteza e modelagem de qualidade da água do Rio Uberaba, Minas Gerais

Mateus

Gonçalves

Júnior

et al. 2015

Rev. Bras. Ciênc. Ambient. (Online)

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RESUMOO objetivo deste estudo foi avaliar o perfil de oxigênio dissolvido (OD) em um trecho urbano da bacia do Rio Uberaba, identificar as principais fontes poluidoras e sugerir medidas de controle. Para tanto, o estudo foi dividido em cinco fases: (i) avaliação da qualidade da água durante um ano hidrológico; (ii) calibração e validação do modelo de qualidade da água; (iii) análise de sensibilidade dos coeficientes e dos dados de entrada do modelo; (iv) análise de incerteza; e (v) criação de cenários para a tomada de decisão. Os resultados mostraram que o Córrego das Lajes é a principal fonte poluidora do Rio Uberaba. O modelo mostrou-se confiável, uma vez que ele pôde ser calibrado e validado. Com a análise de incerteza foi possível mostrar que a probabilidade de o Rio Uberaba atender ao padrão ambiental exigido para a classe 2 (OD≥5,0 mg.L -1 ) é praticamente nula, mas que ela poderia ser elevada para 75,3% se a carga orgânica lançada no rio fosse removida com uma eficiência de 75%.Palavras-chave: modelagem de qualidade da água; análise de incerteza; Rio Uberaba. ABSTRACTThe objective in this study was to evaluate the Dissolved Oxygen (DO) profile along an urban stretch in Uberaba River basin and identify the main pollution sources. For this, the study was divided in five stages: (i) water quality evaluation during a hydrologic year; (ii) calibration and validation of the water quality model; (iii) sensibility analysis of the coefficient and entrance data for the model; (iv) uncertainty analysis; and (v) creation of decision-making scenarios. The results show that Lajes Stream is the main pollution source of Uberaba River. The model demonstrated to be reliable, once it could be calibrated and validated. Through the uncertainty analysis, it is possible to show that the probability of Uberaba River to attempt the environmental standard demanded for class 2 (DO≥5.0 mg.L -1 ) is practically zero, but it could be raised to 75.3% if the organic polluting load released into the river was decreased in 75%.

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“…Recently, geographic mapping has been increasingly used for epidemiology studies, particularly after the development of geographic information system (GIS) technologies that enable data analysis by means of spatial strategies and more comprehensive visual representation of information. GIS is commonly used in environmental epidemiology to assess exposure to pollutants in air (McEntte and OgnevaHimmelberger 2008), water (Wycisk et al 2003;Paliwal et al 2007), and soil (Jarup 2004).…”

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Association of Nitrogen Compounds in Drinking Water with Incidence of Esophageal Squamous Cell Carcinoma in Shexian, China

Zhang

Cao

Wen

et al. 2012

Tohoku J. Exp. Med.

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The incidence of esophageal squamous cell carcinoma (ESCC), which is the eighth most common malignancy worldwide, is highest in China. The purpose of this study was to investigate the association between nitrogen compounds in drinking water with the incidence of ESCC by geographical spatial analysis. The incidence of ESCC is high in Shexian county, China, and environmental factors, particularly nitrogen-contaminated drinking water, are the main suspected risk factors. This study focuses on three nitrogen compounds in drinking water, namely, nitrates, nitrites, and ammonia, all of which are derived mainly from domestic garbage and agricultural fertilizer. The study surveyed 48 villages in the Shexian area with a total population of 54,716 (661 adults with ESCC and 54,055 non-cancer subjects). Hot-spot analysis was used to identify spatial clusters with a high incidence of ESCC and a high concentration of nitrogen compounds. Logistic regression analysis was used to detect risk factors for ESCC incidence. Most areas with high concentrations of nitrate nitrogen in drinking water had a high incidence of ESCC. Correlation analysis revealed a significant positive relationship between nitrate concentration and ESCC (P = 0.01). Logistic regression analysis also confirmed that nitrate nitrogen has a significantly higher odds ratio. The results indicate that nitrate nitrogen is associated with ESCC incidence in Shexian county. In conclusion, high concentrations of nitrate nitrogen in drinking water may be a significant risk factor for the incidence of ESCC.

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Water quality modelling of the river Yamuna (India) using QUAL2E-UNCAS

Cited by 106 publications

References 10 publications

Water quality analysis of River Yamuna using water quality index in the national capital territory, India (2000–2009)

Water quality analysis of River Yamuna using water quality index in the national capital territory, India (2000–2009)

Análise de incerteza e modelagem de qualidade da água do Rio Uberaba, Minas Gerais

Association of Nitrogen Compounds in Drinking Water with Incidence of Esophageal Squamous Cell Carcinoma in Shexian, China

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