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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Volume 20, issue 7
Hydrol. Earth Syst. Sci., 20, 2811–2825, 2016
https://doi.org/10.5194/hess-20-2811-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Hydrol. Earth Syst. Sci., 20, 2811–2825, 2016
https://doi.org/10.5194/hess-20-2811-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 13 Jul 2016

Research article | 13 Jul 2016

Using dry and wet year hydroclimatic extremes to guide future hydrologic projections

Stephen Oni1,5, Martyn Futter2, Jose Ledesma2, Claudia Teutschbein3, Jim Buttle4, and Hjalmar Laudon1 Stephen Oni et al.
  • 1Department of Forest Ecol. Manage., Swedish University of Agricultural Sciences, 901 83, Umeå, Sweden
  • 2Department of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences, 750 07, Uppsala, Sweden
  • 3Department of Earth Sciences, Uppsala University, Villavagen 16, 752 36, Uppsala, Sweden
  • 4Department of Geography, Trent University, 1600 West Bank Drive, Peterborough, ON, K9J 7B8, Canada
  • 5Department of Biology, Trent University, 1600 West Bank Drive, Peterborough, ON, K9J 7B8, Canada

Abstract. There are growing numbers of studies on climate change impacts on forest hydrology, but limited attempts have been made to use current hydroclimatic variabilities to constrain projections of future climatic conditions. Here we used historical wet and dry years as a proxy for expected future extreme conditions in a boreal catchment. We showed that runoff could be underestimated by at least 35 % when dry year parameterizations were used for wet year conditions. Uncertainty analysis showed that behavioural parameter sets from wet and dry years separated mainly on precipitation-related parameters and to a lesser extent on parameters related to landscape processes, while uncertainties inherent in climate models (as opposed to differences in calibration or performance metrics) appeared to drive the overall uncertainty in runoff projections under dry and wet hydroclimatic conditions. Hydrologic model calibration for climate impact studies could be based on years that closely approximate anticipated conditions to better constrain uncertainty in projecting extreme conditions in boreal and temperate regions.

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This paper presents an important framework to improve hydrologic projections in cold regions. Hydrologic modelling/projections are often based on model calibration to long-term data. Here we used dry and wet years as a proxy to quantify uncertainty in projecting hydrologic extremes. We showed that projections based on long-term data could underestimate runoff by up to 35% in boreal regions. We believe the hydrologic modelling community will benefit from new insights derived from this study.
This paper presents an important framework to improve hydrologic projections in cold regions....
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