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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Volume 16, issue 11
Hydrol. Earth Syst. Sci., 16, 4343–4360, 2012
https://doi.org/10.5194/hess-16-4343-2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.
Hydrol. Earth Syst. Sci., 16, 4343–4360, 2012
https://doi.org/10.5194/hess-16-4343-2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 22 Nov 2012

Research article | 22 Nov 2012

Quantifying different sources of uncertainty in hydrological projections in an Alpine watershed

C. Dobler1, S. Hagemann2, R. L. Wilby3, and J. Stötter1 C. Dobler et al.
  • 1Institute of Geography, Innsbruck, Austria
  • 2Max Planck Institute for Meteorology, Hamburg, Germany
  • 3Department of Geography, Loughborough, UK

Abstract. Many studies have investigated potential climate change impacts on regional hydrology; less attention has been given to the components of uncertainty that affect these scenarios. This study quantifies uncertainties resulting from (i) General Circulation Models (GCMs), (ii) Regional Climate Models (RCMs), (iii) bias-correction of RCMs, and (iv) hydrological model parameterization using a multi-model framework. This consists of three GCMs, three RCMs, three bias-correction techniques, and sets of hydrological model parameters. The study is performed for the Lech watershed (~ 1000 km2), located in the Northern Limestone Alps, Austria. Bias-corrected climate data are used to drive the hydrological model HQsim to simulate runoff under present (1971–2000) and future (2070–2099) climate conditions. Hydrological model parameter uncertainty is assessed by Monte Carlo sampling. The model chain is found to perform well under present climate conditions. However, hydrological projections are associated with high uncertainty, mainly due to the choice of GCM and RCM. Uncertainty due to bias-correction is found to have greatest influence on projections of extreme river flows, and the choice of method(s) is an important consideration in snowmelt systems. Overall, hydrological model parameterization is least important. The study also demonstrates how an improved understanding of the physical processes governing future river flows can help focus attention on the scientifically tractable elements of the uncertainty.

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