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Intercomparison of climate change impacts in 12 large river basins: overview of methods and summary of results

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Abstract

This paper introduces the Special Issue “Hydrological Model Intercomparison for Climate Impact Assessment”. We describe the river basins used as case studies, the input data, the hydrological models, and the climate scenarios applied in the multi-model framework. We also summarize the main results of the papers contained in this Special Issue.

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References

  • Arheimer B et al (2012) Water and nutrient simulations using the HYPE model for Sweden vs. the Baltic Sea basin—influence of input-data quality and scale. Hydrol Res 43(4):315–329

    Article  Google Scholar 

  • Arnold JG et al (1993) A comprehensive surface-groundwater flow model. J Hydrol 142:47–69

    Article  Google Scholar 

  • Arnold JG et al (1998) Large area hydrologic modeling and assessment part I: model development. J Am Water Resour Assoc 34:73–89

    Article  Google Scholar 

  • Bergström S, Forsman A (1973) Development of a conceptual deterministic rainfall-runoff model. Nord Hydrol 4:147–170

    Google Scholar 

  • Boyle DP (2001) Multicriteria calibration of hydrological models. PhD Dissertation. Dep Hydrol Water Resour Univ Ariz, Tucson

  • Christensen NS, Lettenmaier DP (2007) A multimodel ensemble approach to assessment of climate change impacts on the hydrology and water resources of the Colorado River Basin. Hydrol Earth Syst Sci 11:1417–1434

    Article  Google Scholar 

  • Donnelly C et al (2015) Using flow signatures and catchment similarities to evaluate a multi-basin model (E-HYPE) across Europe. Hydrol Sci J. doi:10.1080/02626667.2015.1027710

    Google Scholar 

  • Eisner S et al. (2016) An ensemble analysis of climate change impacts on streamflow seasonality across 11 large river basins. Clim Change. doi:10.1007/s10584-016-1844-5

  • Flörke M et al (2013) Domestic and industrial water uses of the past 60 years as a mirror of socio-economic development: a global simulation study. Glob Environ Chang 23(1):144–156

    Article  Google Scholar 

  • Gassman PW et al (2014) Applications of the SWAT model special section: overview and insights. J Environ Qual 1–8. Doi:10.2134/jeq2013.11.0466

  • Gelfan A et al (2015) Large-basin hydrological response to climate model outputs: uncertainty caused by internal atmospheric variability. Hydrol Earth Syst Sci 19:2737–2754

    Article  Google Scholar 

  • Gelfan A et al (2016) Climate change impact on the water regime of two great arctic rivers: modeling and uncertainty issues. Clim Change. doi:10.1007/s10584-016-1710-5

    Google Scholar 

  • Gosling S et al (2016) A comparison of changes in river runoff from multiple global and catchment-scale hydrological models under global warming scenarios of 1°C, 2°C and 3°C. Clim Change. doi:10.1007/s10584-016-1773-3

    Google Scholar 

  • Haddeland I et al (2014) Global water resources affected by human interventions and climate change. Proc Natl Acad Sci USA 111(9):3251–3256

    Article  Google Scholar 

  • Hamlet AF, Lettenmaier DP (1999) Effects of climate change on hydrology and water resources in the Columbia River Basin. J Am Water Resour Assoc 35:1597–1623

    Article  Google Scholar 

  • Hattermann F. et al. (2016) Cross-scale intercomparison of climate change impacts simulated by regional and global hydrological models in eleven large river basins. Clim Change. doi:10.1007/s10584-016-1829-4

  • Herman JD et al (2013) Time-varying sensitivity analysis clarifies the effects of watershed model formulation on model behavior. Water Resour Res 49:1400–1414

    Article  Google Scholar 

  • Huang S et al (2016) Evaluation of an ensemble of regional hydrological models in 12 large-scale river basins worldwide. Clim Change. doi:10.1007/s10584-016-1841-8

    Google Scholar 

  • Krysanova V, White M (2015) Advances in water resources assessment with SWAT—an overview. Hydrol Sci J 60(5):771–783

    Google Scholar 

  • Krysanova V et al (1989) Simulation modelling of the coastal waters pollution from agricultural watershed. Ecol Model 49:7–29

    Article  Google Scholar 

  • Krysanova V et al (1998) Development and test of a spatially distributed hydrological/water quality model for mesoscale watersheds. Ecol Model 106:261–289

    Article  Google Scholar 

  • Krysanova V et al (1999) Modelling river discharge for large drainage basins: from lumped to distributed approach. Hydrol Sci J 44:313–331

    Article  Google Scholar 

  • Krysanova V et al (2015) Modelling climate and land use change impacts with SWIM: lessons learnt from multiple applications. Hydrol Sci J 60(4):606–635

    Article  Google Scholar 

  • Kumar R et al (2013a) Implications of distributed hydrologic model parameterization on water fluxes at multiple scales and locations. Water Resour Res 49(1):360–379

    Article  Google Scholar 

  • Kumar R et al (2013b) Towards computationally efficient large-scale hydrologic predictions with a multiscale regionalization scheme. Water Resour Res 49(9):5700–5714

    Article  Google Scholar 

  • Liang X et al (1994) A simple hydrologically based model of land surface water and energy fluxes for general circulation models. J Geophys Res 99:14415–14428

    Article  Google Scholar 

  • Lindström G et al (2010) Development and test of the HYPE (Hydrological Predictions for the Environment) model—a water quality model for different spatial scales. Hydrol Res 41(3–4):295–319

    Article  Google Scholar 

  • Menzel L et al (2006) Impact of climate change on the regional hydrology—scenario-based modelling studies in the German Rhine catchment. Nat Hazards 38:45–61

    Article  Google Scholar 

  • Mishra V et al (2016) Multimodel assessment of sensitivity and uncertainty of evapotranspiration and a proxy for available water resources under climate change. Clim Chang (in press). This SI

  • Moore RJ (1985) The probability-distributed principle and runoff production at point and basin scales. Hydrol Sci J 30(2):273–297

    Article  Google Scholar 

  • Motovilov YG (2013) ECOMAG: a distributed model of runoff formation and pollution transformation in river basins solution. IAHS Publ 361:227–234

    Google Scholar 

  • Motovilov YG et al (1999) Validation of a distributed hydrological model against spatial observation. Agric For Meteorol 98–99:257–277

    Article  Google Scholar 

  • Nash JE, Sutcliffe JV (1970) River flow forecasting through conceptual models, part I—a discussion of principles. J Hydrol 10:282–290

    Article  Google Scholar 

  • Neitsch SL et al (2011) Soil & water assessment tool theoretical documentation version 2009. Texas Water Resources Institute Technical Report No. 406 Texas A&M University System College Station, TX, pp. 647

  • Pechlivanidis I, Arheimer B (2015) Large-scale hydrological modelling by using modified PUB recommendations: the India-HYPE case. Hydrol Earth Syst Sci Discuss 12:2885–2944

    Article  Google Scholar 

  • Pechlivanidis I et al (2016) Analysis of hydrological extremes at different hydro-climatic regimes under present and future conditions. Clim Change. doi:10.1007/s10584-016-1723-0

    Google Scholar 

  • Rakovec O et al (2015) Multiscale and multivariate evaluation of water fluxes and states over European river basins. J Hydrometeorol. doi:10.1175/JHM-D-15-0054.1

    Google Scholar 

  • Samaniego L et al (2010) Multiscale parameter regionalization of a grid-based hydrologic model at the mesoscale. Water Resour Res 46:W05523. doi:10.1029/2008WR007327

    Google Scholar 

  • Samaniego L et al (2016) Propagation of forcing and model uncertainties on to hydrological drought characteristics in a multi-model century-long experiment in large river basins. Clim Change. doi:10.1007/s10584-016-1778-y

    Google Scholar 

  • Schewe J et al (2014) Multimodel assessment of water scarcity under climate change. Proc Natl Acad Sci USA 111(9):3245–3250

    Article  Google Scholar 

  • Schneider C et al (2013) How will climate change modify river flow regimes in Europe? HESS 17(1):325–339. doi:10.5194/hess-17-325-2013

    Google Scholar 

  • Strauch M et al (2016) Adjustment of global precipitation data for enhanced hydrologic modelling of tropical Andean watersheds. Clim Change. doi:10.1007/s10584-016-1706-1

    Google Scholar 

  • Su B et al (2016) Impacts of climate change on streamflow in the upper Yangtze River basin. Clim Change. doi:10.1007/s10584-016-1852-5

  • Teklesadik AD et al (2016) Intercomparison of hydrological impacts of climate change on the Upper Blue Nile basin using ensemble of hydrological models and global climate models. Clim Chang (in press). This SI

  • Verzano K (2009) Climate change impacts on flood related hydrological processes: Further development and application of a global scale hydrological model, no. 71–2009 in Reports on Earth System Science, 71. Max Planck Institute for Meteorology, Hamburg, Germany

  • Vetter T et al (2015) Multi-model climate impact assessment and intercomparison for three large-scale river basins on three continents. Earth Syst Dyn 6:17–43

    Article  Google Scholar 

  • Vetter T et al (2016) Evaluation of sources of uncertainty in projected hydrological changes under climate change in 12 large-scale river basins. Clim Change. doi:10.1007/s10584-016-1794-y

    Google Scholar 

  • Vrugt JA et al (2005) Improved treatment of uncertainty in hydrologic modeling: combining the strengths of global optimization and data assimilation. Water Resour Res 41:W01017. doi:10.1029/2004WR003059

    Article  Google Scholar 

  • Wang X et al (2016) Analysis of multi-dimensional hydrological alterations under climate change for four major river basins in different climate zones. Clim Change. doi:10.1007/s10584-016-1843-6

    Google Scholar 

  • Warszawski L et al (2014) The Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP): project framework. Proc Natl Acad Sci USA 111(9):3228–3232

    Article  Google Scholar 

  • Weedon GP et al (2011) Creation of the WATCH forcing data and its use to assess global and regional reference crop evaporation over land during the twentieth century. J Hydrometeorol 12:823–848

    Article  Google Scholar 

Download references

Acknowledgements

We are grateful to ISI-MIP for the general support of our regional-scale water sector team and for delivering climate scenarios, and to GRDC for providing discharge data. Many thanks to Shaochun Huang, David Stevens and Hannah Haacke for their help in the preparation of Figs. 2 and 3 and the analysis of climate scenarios.

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Authors and Affiliations

  1. Potsdam Institute for Climate Impact Research, Potsdam, Germany

    Valentina Krysanova & Fred F. Hattermann

Authors
  1. Valentina Krysanova
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  2. Fred F. Hattermann
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Correspondence to Valentina Krysanova.

Additional information

This article is part of a Special Issue on “Hydrological Model Intercomparison for Climate Impact Assessment” edited by Valentina Krysanova and Fred Hattermann.

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Krysanova, V., Hattermann, F.F. Intercomparison of climate change impacts in 12 large river basins: overview of methods and summary of results. Climatic Change 141, 363–379 (2017). https://doi.org/10.1007/s10584-017-1919-y

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