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Possibilistic uncertainty analysis of a conceptual model of snowmelt runoff

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Author(s): A. P. Jacquin

Journal: Hydrology and Earth System Sciences Discussions
ISSN 1812-2108

Volume: 7;
Issue: 2;
Start page: 2053;
Date: 2010;
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ABSTRACT
This study presents the analysis of predictive uncertainty of a conceptual type snowmelt runoff model. The method applied uses possibilistic rather than probabilistic calculus for the evaluation of predictive uncertainty. Possibility theory is an information theory meant to model uncertainties caused by imprecise or incomplete knowledge about a real system rather than by randomness. A snow dominated catchment in the Chilean Andes is used as case study. Predictive uncertainty arising from parameter uncertainties of the watershed model is assessed. Model performance is evaluated according to several criteria, in order to define the possibility distribution of the model representations. The likelihood of the simulated glacier mass balance and snow cover are used for further assessing model credibility. Possibility distributions of the discharge estimates and prediction uncertainty bounds are subsequently derived. The results of the study indicate that the use of additional information allows a reduction of predictive uncertainty. In particular, the assessment of the simulated glacier mass balance and snow cover helps to reduce the width of the uncertainty bounds without a significant increment in the number of unbounded observations.
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Tango Jona
Tangokurs Rapperswil-Jona