Water Resources

, Volume 46, Supplement 1, pp S145–S154 | Cite as

Projecting Changes in Russian Northern River Runoff due to Possible Climate Change during the 21st Century: A Case Study of the Northern Dvina, Taz and Indigirka Rivers

  • O. N. NasonovaEmail author
  • Ye. M. Gusev
  • E. E. Kovalev
  • G. V. Ayzel
  • K. M. Panysheva


Projected changes in river runoff due to possible climate change during the 21st century were simulated with making use of a physically-based land surface model SWAP and meteorological projections simulated by five Global Climate Models (GCMs) for each of four RCP scenarios. The Northern Dvina, Indigirka, and Taz river basins were used in the study. For each basin, 20 projections of changes in climatic river runoff were obtained for three climatic periods of the 21st century. The projected changes in climatic river runoff were analyzed together with the projected changes in climatic precipitation, incoming shortwave and longwave radiation, and evapotranspiration. The obtained hydrological projections were used to estimate their uncertainties resulting from the application of different GCMs and RCP scenarios.


ISI-MIP land surface model SWAP river runoff evapotranspiration precipitation incoming radiation uncertainty GCMs RCP scenarios 



We are grateful to ISI-MIP regional-scale water sector organizers for providing with data and materials. River runoff data were kindly provided by the Global Runoff Data Centre (GRDC), D–56068 Koblenz, Germany.


The study was supported by the Russian Science Foundation (project no. 16-17-10 039).


  1. 1.
    Duan, Q., Sorooshian, S., and Gupta, V.K., Effective and efficient global optimization for conceptual rainfall runoff models, Water Resour. Res., 1992, vol. 28, no. 4, pp. 1015–1031.CrossRefGoogle Scholar
  2. 2.
    Gelfan, A., Gustafsson, D., Motovilov,Yu., Arheimer, B., Kalugin, A., Krylenko, I., and Lavrenov, A., Climate change impact on water regime of two great Arctic rivers: modeling and uncertainty issues, Climatic Change, 2017, vol. 141, pp. 499–515.CrossRefGoogle Scholar
  3. 3.
    Gelfan, A., Semenov, V.A., Gusev, E., Motovilov, Y., Nasonova, O., Krylenko, I., and Kovalev, E., Largebasin hydrological response to climate model outputs: uncertainty caused by internal atmospheric variability, Hydrol. Earth Syst. Sci., 2015, vol. 19, pp. 2737–2754.CrossRefGoogle Scholar
  4. 4.
    Gosling, S.N., Taylor, R.G., Arnell, N.W., and Todd, M.C., A comparative analysis of projected impacts of climate change on river runoff from global and catchment-scale hydrological models, Hydrol. Earth Syst. Sci., 2011, vol. 15, pp. 279–294.CrossRefGoogle Scholar
  5. 5.
    Gusev, E.M. and Nasonova, O.N., Modelirovanie teplo- i vlagoobmena poverkhnosti sushi s atmosferoi (Modelling Heat and Water Exchange between the Land Surface and the Atmosphere), Moscow: Nauka, 2010.Google Scholar
  6. 6.
    Gusev, E.M., Nasonova, O.N., Dzhogan, L.Ya., and Aizel, G.V., Modeling streamflow of the Olenek and Indigirka rivers using Land Surface Model SWAP, Water Resour., 2013, vol. 40, no. 5, pp.535–543.CrossRefGoogle Scholar
  7. 7.
    Gusev, E.M., Nasonova, O.N., Dzhogan, L.Ya., and Aizel’, G.V., Simulating the formation of river runoff and snow cover in the Northern West Siberia, Water Resour., 2015, vol. 42, no. 4, pp. 460–467.CrossRefGoogle Scholar
  8. 8.
    Gusev, E.M., Nasonova, O.N., Dzhogan, L.Ya., and Kovalev, E.E, Northern Dvina runoff simulation using land-surface model SWAP and global databases, Water Resour., 2011, vol. 38., no. 4, pp. 470–483.CrossRefGoogle Scholar
  9. 9.
    Gusev, Ye.M., Nasonova, O.N., Kovalev, E.E., and Aizel, G.V., Modelling river runoff and estimating its weather-related uncertainty for 11 large-scale rivers located in different regions of the globe, Hydrol. Res., 2018, vol. 49, no. 4, pp. 1072–1087.CrossRefGoogle Scholar
  10. 10.
    Gusev, E.M., Nasonova, O.N., Kovalev, E.E, and Ayzel,G.V., Modelling water balance components of river basins located in different regions of the globe, Water Resour., 2018, vol. 45, Supplement 2, pp. 53–64.CrossRefGoogle Scholar
  11. 11.
    Gusev, E.M., Nasonova, O.N., Kovalev, E.E, and Ayzel’, G.V., Possible climate change impact on river runoff in the different regions of the globe, Russ. Meteorol. Hydrol., 2018, vol. 43, no. 6, pp. 397–403.CrossRefGoogle Scholar
  12. 12.
    Hempel, S., Frieler, K., Warszawski, L., Schewe, J., and Piontek, F., A trend-preserving bias correction— the ISI-MIP approach, Earth Syst. Dynam., 2013, vol. 4, no. 2, pp. 219–236.CrossRefGoogle Scholar
  13. 13.
    Krysanova, V. and Hattermann, F.F., Intercomparison of climate change impacts in 12 large river basins: overview of methods and summary of results, Clim. Change, 2017, vol. 141, pp. 363–379.CrossRefGoogle Scholar
  14. 14.
    Nasonova, O.N., Gusev, Ye.M., and Kovalev, Ye.E., Investigating the ability of a land surface model to simulate streamflow with the accuracy of hydrological models: a case study using MOPEX materials, J. Hydrometeor., 2009, vol. 10, no 5, pp. 1128–1150.CrossRefGoogle Scholar
  15. 15.
    Nasonova, O.N., Gusev, Ye.M., Kovalev, E.E., and Ayzel, G.V., Climate change impact on streamflow in large-scale river basins: projections and their uncertainties sourced from GCMs and RCP scenarios, Proc. IAHS, 2018, no 379, pp. 139–144.CrossRefGoogle Scholar
  16. 16.
    Nasonova, O.N., Gusev, Ye.M., Volodin, E.M., and Kovalev, E.E., Application of the land surface model SWAP and global climate model INMCM4.0 for projecting runoff of northern Russian rivers. 2. Projections and their uncertainties, Water Resour., 2018, vol. 45, Supplement 2, pp. 85–92.CrossRefGoogle Scholar
  17. 17.
    Nash, J.E. and Sutcliffe, J.V., River flow forecasting through conceptual models: 1 A discussion of principles, J. Hydrol., 1970, vol. 10, no. 3, pp. 282–290.CrossRefGoogle Scholar
  18. 18.
    Vetter, T., Reinhardt, J., Flörke, M., van Griensven, A., Hattermann, F., Huang, S., Koch, H., Pechlivanidis, I.G., Plötner, S., Seidou, O., Su, B., Vervoort, R.W., and Krysanova, V., Evaluation of sources of uncertainty in projected hydrological changes under climate change in 12 large-scale river basins, Clim. Change, 2017, vol. 141, pp. 419–433.CrossRefGoogle Scholar
  19. 19.
    Warszawski, L., Frieler, K., Huber, V., Piontek, F., Serdeczny, O., and Schewe, J., The inter-sectoral impact model intercomparison project (ISI–MIP): project framework, PNAS, 2013, vol. 111, no. 9, pp. 3228–3232.CrossRefGoogle Scholar
  20. 20.
    Weedon, G.P., Gomes, S., Viterbo, P., Shuttleworth, W.J., Blyth, E., Oesterle, H., Adam, J.C., Bellouin, N., Boucher, O., and Best, M., Creation of the WATCH Forcing Data and its uses to assess global and regional reference crop evaporation over land during the twentieth century, J. Hydrometeorol., 2011, vol. 12, pp. 823–848.CrossRefGoogle Scholar
  21. 21.
    Wilby, R.L. and Harris, I., A framework for assessing uncertainties in climate change impacts: low-flow scenarios for the River Thames, UK, Water Resour. Res., 2006, vol. 42, no. 2, W02419.CrossRefGoogle Scholar

Copyright information

© Pleiades Publishing, Ltd. 2019

Authors and Affiliations

  • O. N. Nasonova
    • 1
    Email author
  • Ye. M. Gusev
    • 1
  • E. E. Kovalev
    • 1
  • G. V. Ayzel
    • 1
  • K. M. Panysheva
    • 1
    • 2
  1. 1.Water Problems Institute, Russian Academy of SciencesMoscowRussia
  2. 2.Moscow State University, Faculty of GeographyMoscowRussia

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