A fast and effective parameterization of water quality models
Water quality (WQ) models parameterization remains a challenging task, as these models are typically characterized by a high number of parameters. The objective of this study was to present a solution to the WQ parameterization problem by the use of a fast sensitivity analysis (SA) method and a manu...
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Veröffentlicht in: | Environmental modelling & software : with environment data news 2022-03, Vol.149, p.105331, Article 105331 |
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Sprache: | eng |
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Zusammenfassung: | Water quality (WQ) models parameterization remains a challenging task, as these models are typically characterized by a high number of parameters. The objective of this study was to present a solution to the WQ parameterization problem by the use of a fast sensitivity analysis (SA) method and a manual calibration. For this purpose, we applied the simple screening LH-OAT method to the conceptual WQ model of the River Dender, Belgium. To evaluate the effectiveness of LH-OAT to identify the influential parameters, the advanced PAWN method was applied. A manual calibration was done using the influential parameters.
LH-OAT provided a parameter ranking that was very similar to the one of PAWN but in a much more efficient way. The Bayesian uncertainty assessment showed the effectiveness of the LH-OAT results. To conclude, a fast screening method is preferred over an advanced SA method to identify the influential parameters for the calibration.
•Water quality models parameterization is still a challenging task.•The use of a fast sensitivity analysis (SA) method and a manual calibration is proposed as a solution to the parameterization problem.•LH-OAT provides a parameter ranking that is very similar to the one of PAWN but in a much more efficient way.•For parameter screening, a simple method is preferred over an advanced method. |
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ISSN: | 1364-8152 1873-6726 |
DOI: | 10.1016/j.envsoft.2022.105331 |