Archief Prof. Ir. J.J. Peters

Over het archief

In 2012 verloren we Jean Jacques Peters, voormalig ingenieur van het Waterbouwkundig Laboratorium (1964 tot 1979) en internationaal expert in sedimenttransport, rivierhydraulica en -morfologie. Als eerbetoon aan hem hebben we potamology (http://www.potamology.com/) gecreëerd, een virtueel gedenkarchief dat als doel heeft om zijn manier van denken en morfologische aanpak van rivierproblemen in de wereld in stand te houden en te verspreiden.

Het merendeel van z’n werk hebben we toegankelijk gemaakt via onderstaande zoekinterface.

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A fast and effective parameterization of water quality models Khorashadi Zadeh, F.; Nossent, J.; Taddesse Woldegiorgis, B.; Bauwens, W.; Van Griensven, A. (2022). A fast and effective parameterization of water quality models. Environ. Model. Softw. 149: 105331. https://dx.doi.org/10.1016/j.envsoft.2022.105331 In: Environmental Modelling & Software. Elsevier: Oxford. ISSN 1364-8152; e-ISSN 1873-6726

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Beschikbaar in	Auteurs
Waterbouwkundig Laboratorium: Open Repository 378390 [ OWA ] Waterbouwkundig Laboratorium: Non-open access 371209 [ aanvragen ]

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Trefwoorden

Numerical modelling Water management > Hydrology > Conceptual models Water management > Statistics > Sensitivity analysis Water management > Statistics > Uncertainty analysis Water management > Water quality > Conceptual models

Author keywords

Parameterization; Sensitivity analysis; Uncertainty analysis; DREAM(ZS); Error model

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Ontwikkelen van conceptuele modellen

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Auteurs		Top
Khorashadi Zadeh, F. Nossent, J. Taddesse Woldegiorgis, B.	Bauwens, W. Van Griensven, A.

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Abstract

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.

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