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Earth System Dynamics An interactive open-access journal of the European Geosciences Union
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Volume 6, issue 1
Earth Syst. Dynam., 6, 267-285, 2015
https://doi.org/10.5194/esd-6-267-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

Special issue: Intersectoral Impact Model Intercomparison Project (ISI-MIP)

Earth Syst. Dynam., 6, 267-285, 2015
https://doi.org/10.5194/esd-6-267-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 18 May 2015

Research article | 18 May 2015

Future hydrological extremes: the uncertainty from multiple global climate and global hydrological models

I. Giuntoli1,2,3, J.-P. Vidal3, C. Prudhomme2, and D. M. Hannah1 I. Giuntoli et al.
  • 1School of Geography, Earth & Environmental Sciences, University of Birmingham, Birmingham B15 2TT, UK
  • 2Centre for Ecology and Hydrology, Wallingford OX10 8BB, UK
  • 3Irstea, UR HHLY Hydrology-Hydraulics, Lyon, France

Abstract. Projections of changes in the hydrological cycle from global hydrological models (GHMs) driven by global climate models (GCMs) are critical for understanding future occurrence of hydrological extremes. However, uncertainties remain large and need to be better assessed. In particular, recent studies have pointed to a considerable contribution of GHMs that can equal or outweigh the contribution of GCMs to uncertainty in hydrological projections. Using six GHMs and five GCMs from the ISI-MIP multi-model ensemble, this study aims: (i) to assess future changes in the frequency of both high and low flows at the global scale using control and future (RCP8.5) simulations by the 2080s, and (ii) to quantify, for both ends of the runoff spectrum, GCMs and GHMs contributions to uncertainty using a two-way ANOVA. Increases are found in high flows for northern latitudes and in low flows for several hotspots. Globally, the largest source of uncertainty is associated with GCMs, but GHMs are the greatest source in snow-dominated regions. More specifically, results vary depending on the runoff metric, the temporal (annual and seasonal) and regional scale of analysis. For instance, uncertainty contribution from GHMs is higher for low flows than it is for high flows, partly owing to the different processes driving the onset of the two phenomena (e.g. the more direct effect of the GCMs' precipitation variability on high flows). This study provides a comprehensive synthesis of where future hydrological extremes are projected to increase and where the ensemble spread is owed to either GCMs or GHMs. Finally, our results underline the need for improvements in modelling snowmelt and runoff processes to project future hydrological extremes and the importance of using multiple GCMs and GHMs to encompass the uncertainty range provided by these two sources.

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We assessed future changes in high and low flows globally using runoff projections from global hydrological models (GHMs) driven by global climate models (GCMs) under the RCP8.5 scenario. Further, we quantified the relative size of uncertainty from GHMs and from GCMs using ANOVA. We show that GCMs are the major contributors to uncertainty overall, but GHMs increase their contribution for low flows and can equal or outweigh GCM uncertainty in snow-dominated areas for both high and low flows.
We assessed future changes in high and low flows globally using runoff projections from global...
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