Integration of SWAT and QUAL2K for water quality modeling in a data scarce basin of Cau River basin in Vietnam

Bui, HH; Ha, NH; Nguyen, TND; Nguyen, AT; Pham, TTH; Kandasamy, J; Nguyen, TV

Integration of SWAT and QUAL2K for water quality modeling in a data scarce basin of Cau River basin in Vietnam

Bui, HH Ha, NH Nguyen, TND Nguyen, AT Pham, TTH Kandasamy, J Nguyen, TV

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Publication Type:: Journal Article
Citation:: Ecohydrology and Hydrobiology, 2019, 19 (2), pp. 210 - 223
Issue Date:: 2019-04-01

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Field	Value	Language
dc.contributor.author	Bui, HH	en_US
dc.contributor.author	Ha, NH	en_US
dc.contributor.author	Nguyen, TND	en_US
dc.contributor.author	Nguyen, AT	en_US
dc.contributor.author	Pham, TTH	en_US
dc.contributor.author	Kandasamy, J	en_US
dc.contributor.author	Nguyen, TV	en_US
dc.date.available	2020-05-25T19:08:50Z
dc.date.issued	2019-04-01	en_US
dc.identifier.citation	Ecohydrology and Hydrobiology, 2019, 19 (2), pp. 210 - 223	en_US
dc.identifier.issn	1642-3593	en_US
dc.identifier.uri	http://hdl.handle.net/10453/131870
dc.description.abstract	© 2019 European Regional Centre for Ecohydrology of the Polish Academy of Sciences Water quality modeling in a river basin often faces the problem of having a large number of parameters yet limited available data. The important inputs to the water quality model are pollution concentrations and discharge from river tributaries, lateral inflows and related pollution load from different sources along the river. In general, such an extensive data set is rarely available, especially for data scarce basins. This makes water quality modeling more challenging. However, integration of models may be able to fill this data gap. Selection of models should be made based on the data that is available for the river basin. For the case of Cau River basin, the SWAT and QUAL2K models were selected. The outputs of SWAT model for lateral inflows and discharges of ungauged tributaries, and the observed pollutant concentrations data and estimated pollution loads of sub-watersheds were used as inputs to the water quality model QUAL2K. The resulting QUAL2K model was calibrated and validated using recent water quality data for two periods in 2014. Four model performance ratings PBIAS, NSE, RSR and R2 were used to evaluate the model results. PBIAS index was chosen for water quality model evaluation because it more adequately accounted for the large uncertainty inherent in water quality data. In term of PBIAS, the calibration and validation results for Cau River water quality model were in the “very good” performance range with ǀPBIASǀ < 15%. The obtained results could be used to support water quality management and control in the Cau River basin.	en_US
dc.relation.ispartof	Ecohydrology and Hydrobiology	en_US
dc.relation.isbasedon	10.1016/j.ecohyd.2019.03.005	en_US
dc.subject.classification	Marine Biology & Hydrobiology	en_US
dc.title	Integration of SWAT and QUAL2K for water quality modeling in a data scarce basin of Cau River basin in Vietnam	en_US
dc.type	Journal Article
utslib.citation.volume	2	en_US
utslib.citation.volume	19	en_US
utslib.for	0904 Chemical Engineering	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Civil and Environmental Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CTWW - Centre for Technology in Water and Wastewater Treatment
utslib.copyright.status	open_access
pubs.issue	2	en_US
pubs.publication-status	Published	en_US
pubs.volume	19	en_US

Abstract:

© 2019 European Regional Centre for Ecohydrology of the Polish Academy of Sciences Water quality modeling in a river basin often faces the problem of having a large number of parameters yet limited available data. The important inputs to the water quality model are pollution concentrations and discharge from river tributaries, lateral inflows and related pollution load from different sources along the river. In general, such an extensive data set is rarely available, especially for data scarce basins. This makes water quality modeling more challenging. However, integration of models may be able to fill this data gap. Selection of models should be made based on the data that is available for the river basin. For the case of Cau River basin, the SWAT and QUAL2K models were selected. The outputs of SWAT model for lateral inflows and discharges of ungauged tributaries, and the observed pollutant concentrations data and estimated pollution loads of sub-watersheds were used as inputs to the water quality model QUAL2K. The resulting QUAL2K model was calibrated and validated using recent water quality data for two periods in 2014. Four model performance ratings PBIAS, NSE, RSR and R2 were used to evaluate the model results. PBIAS index was chosen for water quality model evaluation because it more adequately accounted for the large uncertainty inherent in water quality data. In term of PBIAS, the calibration and validation results for Cau River water quality model were in the “very good” performance range with ǀPBIASǀ < 15%. The obtained results could be used to support water quality management and control in the Cau River basin.

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http://hdl.handle.net/10453/131870