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

Abstract

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

Water quality modeling in the Paraibuna River in Juiz de Fora/MG: diagnosis and prognosis

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Stream water quality modelling for pollution load capacity in Roshi river- rural Nepal

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Water Quality Risk Assessment for the Laoguanhe River of China Using a Stochastic Simulation Method

“…Thus, it is generally conluded that the model can form the basis of water quality management (Kannel et al, 2007b;Oliveira et al, 2012). In many studies, DO, BOD, nitrogen, phosphorus and COD have been used as typical indicators to model water quality variations of streams and rivers (Kannel et al, 2007a;Camargo et al, 2010;Nakhaei and Etemad-Shahidi, 2012). The latest QUAL2Kw (i.e., QUAL2Kw version 6) was integrated with non-steady, nonuniform flow using a kinematic wave flow routing approach and has the option to use repeating diel conditions, which is similar to the early version but with either steady or non-steady flows (Department of Ecology of the State of Washington, 2017).…”