Research Article
Global sensitivity analyses for a complex hydrological model applied in an Alpine watershed
Article first published online: 26 SEP 2012
DOI: 10.1002/hyp.9520
Copyright © 2012 John Wiley & Sons, Ltd.
Issue

Hydrological Processes
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Additional Information
How to Cite
Dobler, C. and Pappenberger, F. (2012), Global sensitivity analyses for a complex hydrological model applied in an Alpine watershed. Hydrol. Process.. doi: 10.1002/hyp.9520
Publication History
- Article first published online: 26 SEP 2012
- Accepted manuscript online: 21 AUG 2012 04:55PM EST
- Manuscript Accepted: 1 AUG 2012
- Manuscript Received: 17 JAN 2012
Funded by
- Austrian Climate and Energy Fund
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Keywords:
- Alpine basin;
- hydrological model;
- Morris analysis;
- regional sensitivity analysis;
- sensitivity analysis;
- state-dependent parameter modelling
Abstract
The increasing complexity of hydrological models results in a large number of parameters to be estimated. In order to better understand how these complex models work, efficient screening methods are required in order to identify the most important parameters. This is of particular importance for models that are used within an operational real-time forecasting chain such as HQsim. The objectives of this investigation are to (i) identify the most sensitive parameters of the complex HQsim model applied in the Alpine Lech catchment and (ii) compare model parameter sensitivity rankings attained from three global sensitivity analysis techniques. The techniques presented are the (i) regional sensitivity analysis, (ii) Morris analysis and (iii) state-dependent parameter modelling. The results indicate that parameters affecting snow melt as well as processes in the unsaturated soil zone reveal high significance in the analysed catchment. The snow melt parameters show clear temporal patterns in the sensitivity whereas most of the parameters affecting processes in the unsaturated soil zone do not vary in importance across the year. Overall, the maximum degree day factor (meltfunc_max) has been identified to play a key role within the HQsim model. Although the parameter sensitivity rankings are equivalent between methods for a number of parameters, for several key parameters differing results were obtained. An uncertainty analysis demonstrates that a parameter ranking attained from only one method is subjected to large uncertainty. Copyright © 2012 John Wiley & Sons, Ltd.

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