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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/hess-2019-388
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-2019-388
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 06 Aug 2019

Submitted as: research article | 06 Aug 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Hydrology and Earth System Sciences (HESS).

Historical and future changes in global flood magnitude – evidence from a model-observation investigation

Hong Xuan Do1,2,3, Fang Zhao4,5, Seth Westra1, Michael Leonard1, Lukas Gudmundsson6, Jinfeng Chang7, Philippe Ciais7, Dieter Gerten5,8, Simon N. Gosling9, Hannes Müller Schmied10,11, Tobias Stacke12, Boulange Julien Eric Stanislas13, and Yoshihide Wada14 Hong Xuan Do et al.
  • 1School of Civil, Environmental and Mining Engineering, University of Adelaide, Adelaide, Australia
  • 2Faculty of Environment and Natural Resources, Nong Lam University, Ho Chi Minh City, Vietnam
  • 3School for Environment and Sustainability, University of Michigan, Ann Arbor, Michigan, United States
  • 4School of Geographical Sciences, East China Normal University, Shanghai, China
  • 5Potsdam Institute for Climate Impact Research, Potsdam, Germany
  • 6Institute for Atmospheric and Climate Science, Department of Environmental Systems Science, ETH Zurich, Zurich, Switzerland
  • 7Laboratoire des Sciences du Climat et de l’Environnement, CEA-CNRS-UVSQ/IPSL, Université Paris Saclay, 91191 Gif sur Yvette, France
  • 8Geography Dept., Humboldt-Universität zu Berlin, Berlin, Germany
  • 9School of Geography, University of Nottingham, Nottingham, United Kingdom
  • 10Institute of Physical Geography, Goethe University Frankfurt, Frankfurt am Main, Germany
  • 11Senckenberg Leibnitz Biodiversity and Climate Research Centre (SBiK-F), Frankfurt am Main, Germany
  • 12Max Planck Institute for Meteorology, Hamburg, Germany
  • 13Center for Global Environmental Research, Japan
  • 14International Institute for Applied Systems Analysis, Laxenburg, Austria

Abstract. To improve the understanding of trends in extreme flows related to flood events at the global scale, historical and future changes of annual maximum streamflow are investigated, using a comprehensive streamflow archive and six global hydrological models. The models' capacity to characterise trends in annual maximum streamflow is evaluated across 3,666 river gauge locations over the period from 1971 to 2005, focusing on four aspects of trends over continental and global scale: (i) mean, (ii) standard deviation, (iii) percentage of locations showing significant trends and (iv) spatial pattern. Compared to observed trends, simulated trends driven by observed climate forcing generally have a higher mean, lower spread, and a similar percentage of locations showing significant trends. Models show a moderate capacity to simulate spatial patterns of historical trends, with approximately only 12–25 % of the spatial variance of observed trends across all gauge stations accounted for by the simulations. Interestingly, there are significant differences between trends simulated by GHMs forced with historical climate and forced by bias corrected climate model output during the historical period, suggesting the important role of the stochastic natural (decadal, inter-annual) climate variability. Significant differences were found in simulated flood trend results when averaged only at gauged locations compared to when averaging across all simulated grid cells, highlighting the potential for bias toward well-observed regions in the state-of-understanding of changes in floods. Future climate projections (simulated under RCP2.6 and RCP6.0 greenhouse gas concentration scenario) suggest a potentially high level of change in individual regions, with up to 35 % of cells showing a statistically significant trend (increase or decrease) and greater changes indicated for the higher concentration pathway. Importantly, the observed streamflow database under-samples the percentage of high-risk locations under RCP6.0 greenhouse gas concentration scenario by more than an order of magnitude (0.9 % compared to 11.7 %). This finding indicates a highly uncertain future for both flood-prone communities and decision makers in the context of climate change.

Hong Xuan Do et al.
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Data sets

The Global Streamflow Indices and Metadata (GSIM) archive - Part 1 H. X. Do, L. Gudmundsson, M. Leonard, and S. Westra https://doi.org/10.1594/PANGAEA.887477

The Global Streamflow Indices and Metadata (GSIM) archive - Part 2 L. Gudmundsson, H. X. Do, M. Leonard, and S. Westra https://doi.pangaea.de/10.1594/PANGAEA.887470

Hong Xuan Do et al.
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Short summary
A global comparison between observed and simulated trends in streamflow annual maximum over the 1971–2005 period was presented, using the Global Streamflow Indices and Metadata archive and six global hydrological models available through The Inter-Sectoral Impact Model Intercomparison Project. Streamflow simulations over 2006–2099 period robustly project high flood hazard in several regions. These high flood risk areas, however, are under-sampled by current global streamflow databases.
A global comparison between observed and simulated trends in streamflow annual maximum over the...
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