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Comparison of the PAWN and Sobol’ sensitivity analysis methods for a highly-parameterized hydrological model using SWAT
Khorashadi Zadeh, F.; Sarrazin, F.; Nossent, J.; Pianosi, F.; Van Griensven, A.; Wagener, T.; Bauwens, W. (2015). Comparison of the PAWN and Sobol’ sensitivity analysis methods for a highly-parameterized hydrological model using SWAT, in: E-proceedings of the 36th IAHR World Congress 28 June – 3 July, 2015, The Hague, the Netherlands. pp. [1-4]
In: (2015). E-proceedings of the 36th IAHR World Congress 28 June – 3 July, 2015, The Hague, the Netherlands. IAHR: [s.l.]. , meer
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| Beschikbaar in | Auteurs |
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Documenttype: Congresbijdrage
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| Author keywords |
Global sensitivity analysis; Moment-independent method; Variance-based method; SWAT model |
| Auteurs | | Top |
- Khorashadi Zadeh, F.
- Sarrazin, F.
- Nossent, J., meer
- Pianosi, F.
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- Van Griensven, A.
- Wagener, T.
- Bauwens, W.
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| Abstract |
The high number of parameters is a major problem for complex environmental models as it restricts their application. Therefore, sensitivity analysis (SA) methods, that aim to identify the influential and the non-influential parameters of a model, can be essential for an efficient calibration of these models. The SA indeed allows for a reduction of the number of parameters involved in a calibration procedure, by applying factor fixing (FF) and factor prioritization (FP). In this paper, a density-based Global Sensitivity Analysis (GSA) method -PAWN- is applied to the Soil and Water Assessment Tool (SWAT), a highly-parameterized hydrological simulator. The objective of this study is to compare the newly developed PAWN method with the Sobol’ method, which is a well-established and widely used variance-based SA method. The PAWN method considers the entire model output distribution to describe the output uncertainty while the Sobol’ method implicitly assumes that the variance is a sufficient indicator for this purpose. To this end, 26 water quantity related parameters of a SWAT model of the River Zenne (Belgium) are selected to be ranked, using both the PAWN and the Sobol’ methods. In addition, the two SA methods are evaluated and compared in terms of convergence, the related evolution of the parameter ranking results and required computation cost. |
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