Application of QUAL2Kw for water quality modeling and dissolved oxygen control in the river Bagmati

Kannel, Prakash Raj; Lee, Seockheon; Kanel, Sushil R.; Lee, Young-S.; Ahn, Kyu Hong

doi:10.1007/s10661-006-9255-0

Cited by 46 publications

(30 citation statements)

References 17 publications

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“…O modelo se baseia em equações diferenciais ordinárias para sistemas unidimensionais e de fluxo constante, ou seja, a concentração do material em estudo é homogênea numa mesma seção transversal, além de se enquadrar melhor do que antigos modelos para simular condições de rios com descargas de efluentes difusas. Alguns estudos simularam a variação química das águas superficiais utilizando o modelo QUAL2K, por exemplo, aqueles realizados por (Park & Lee, 2002;USEPA, 2004USEPA, & 2005DNREC, 2005;Kannel et al, 2007;Salvai & Bezdan, 2008).…”

Section: Introdução E Objetivounclassified

Avaliação da qualidade da água e autodepuração do ribeirão do meio, Leme (SP)

Sardinha¹,

Conceição²,

Souza³

et al. 2008

Eng. Sanit. Ambient.

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Section: Introdução E Objetivounclassified

Avaliação da qualidade da água e autodepuração do ribeirão do meio, Leme (SP)

Sardinha¹,

Conceição²,

Souza³

et al. 2008

Eng. Sanit. Ambient.

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“…In order to be sure that the numerical modeling results are correct, validation of applying Q2K has been done with Kannel's data (Kannel et al, 2007). The results correlated with Kannel's performance.…”

Section: The Modeling Informationmentioning

confidence: 99%

Assessing of channel roughness and temperature variations on wastewater quality parameters using numerical modeling

Gholipour¹,

Alamatian²,

Foerstner³

2015

Journal of Applied Sciences and Environmental Management

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Nowadays, problems and barriers to supply adequate water and address environmental issues have caused wastewater treatment (WWT) to be considered a high priority. In light of high costs of WWT, using natural capacities to reduce pollution could be potentially economically significant. In this paper, the impact of varying temperature and channel roughness has been investigated on the wastewater quality parameters using the QUAL2K (Q2K) Numerical Model. The results show, as temperature increases, the reduction rate of Biochemical Oxygen Demand (BOD) is more than the Chemical Oxygen Demand (COD). Also, organic nitrogen (ON), organic phosphorus (P), coliforms, total organic carbon (C), total suspended solids (TSS) and total nitrogen (TN) decrease; but nitrate concentration (NO 3 ) increases. This numerical assessment indicates that the purification rate is greater as temperature rises above 30°C. The results show that by increasing channel roughness, BOD, COD, Particle Organic Matter (POM), organic nitrogen, phosphorus and coliforms have descending trends while inorganic phosphorus and ammonium concentrations have ascending trends. According to the obtained results, nitrate (NO 3 ) has a decreasing trend when the Manning Roughness Coefficient (N) is higher than 0.04 along the channel, but is reduced when "N" is less than 0.04. © JASEM http://dx.doi.org/10.4314/jasem.v19i1.16

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“…The fitness is determined as the reciprocal of the weighted average of the normalized root mean square error (RMSE) of the difference between the model predictions and the observed data for water quality constituents (Kannel et al, 2007). BOD values found for the samples collected in different days (Von Sperling, 2007).…”

Section: Input Datamentioning

confidence: 99%

“…The algae cover and bottom-sediment oxygen demand were both assumed to be 100% (Kannel et al, 2007). The sediment/hyporheic zone thickness, sediment porosity and hyporheic exchange flow were assumed to be 10 cm, 40%, and 5%, respectively (Kannel et al, 2007).…”

Section: Model Implementationmentioning

confidence: 99%

“…To obtain the best adjustment, the modeling system assigns standard weights to various parameters so as to minimize the error between the observed and simulated data. We used a weight of 50 for DOC, because it is the most influential parameter, versus weights of two for pH, BOD 5 , N org , NH 3 , NO 3 , P org , and P inorg ; the other parameters received a weight of 1 (Kannel et al, 2007).…”

Section: Kinetics Parametersmentioning

confidence: 99%

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Water quality prediction using the QUAL2Kw model in a small karstic watershed in Brazil

Camargo¹,

Calijuri²,

Santiago³

et al. 2010

Acta

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Aim: The Tancredo Neves International Airport (TNIA) complex is situated in Brazil's Fidalgo watershed. Since its construction, the TNIA complex has attracted urban development, leading to expansion of the complex and occupation of the surrounding area. However, this area lacks basic infrastructure such as wastewater treatment facilities. This paper had the objectives of calibrating and validating a water quality prediction model and of assessing the capacity of small karstic watersheds to assimilate non-point source pollutant loads; Methods: We used the QUAL2Kw model for modeling the water quality. We performed model calibration for the rainy period then validated the results for the dry period; Results: The model adequately represented the physical, chemical, and hydraulic aspects of the Fidalgo watershed. The pH, EC, TDS, TP, alkalinity and E. coli presented the closest simulation values for the rainy period. For the dry period, the best simulations were obtained for pH, EC, TDS, TP, and alkalinity. We concluded that the calibration and validation periods had similar RMSE values for flow rate, TDS and DOC. The differences were greater for pH, EC, NO 3 , TP, and E. coli. The lowest dissolved oxygen contents obtained during the calibration and validation periods were 5.4 and 4.7 mg.L The conservation of the water resources in this region should therefore consider the adoption of preventive measures such as protecting exposed soils and decreasing the nutrient influx from agricultural and livestock activities.Keywords: water quality, karstic region, modeling, QUAL2Kw, urban pollution.Resumo: Objetivo: O Aeroporto Internacional Tancredo Neves (AITN) está localizado na microbacia do córrego do Fidalgo, Brasil. Desde sua construção, o AITN tem atraído a instalação de indústrias e loteamentos residenciais sem que a região oferecesse condições básicas de infraestrutura. Este trabalho teve por objetivo calibrar e validar modelo de predição da qualidade da água e avaliar a capacidade de assimilação de cargas difusas em microbacia cárstica; Métodos: Utilizou-se o QUAL2Kw para a modelagem da qualidade da água. A calibração do modelo foi realizada no período chuvoso e a validação para o período seco; Resultados: O modelo demonstrou ser capaz de representar com habilidade e flexibilidade os aspectos físicos, químicos e hidráulicos observados na microbacia. Os parâmetros pH, CE, STD, PT, alcalinidade e E. coli apresentaram os melhores ajustes entre as previsões do modelo e os dados observados para o período chuvoso. Para o período seco, os melhores ajustes foram obtidos para pH, EC, TDS, TP e alcalinidade. Os valores de REMQ foram similares entre os períodos para vazão, SDT e OD. As maiores diferenças foram observadas para os parâmetros pH, CE, NO 3

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Application of QUAL2Kw for water quality modeling and dissolved oxygen control in the river Bagmati

Cited by 46 publications

References 17 publications

Avaliação da qualidade da água e autodepuração do ribeirão do meio, Leme (SP)

Avaliação da qualidade da água e autodepuração do ribeirão do meio, Leme (SP)

Assessing of channel roughness and temperature variations on wastewater quality parameters using numerical modeling

Water quality prediction using the QUAL2Kw model in a small karstic watershed in Brazil

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