Climatic Change

, Volume 145, Issue 3–4, pp 289–303 | Cite as

Projecting future nonstationary extreme streamflow for the Fraser River, Canada

  • Rajesh R. ShresthaEmail author
  • Alex J. Cannon
  • Markus A. Schnorbus
  • Francis W. Zwiers


We describe an efficient and flexible statistical modeling framework for projecting nonstationary streamflow extremes for the Fraser River basin in Canada, which is dominated by nival flow regime. The framework is based on an extreme value analysis technique that allows for nonstationarity in annual extreme streamflow by relating it to antecedent winter and spring precipitation and temperature. We used a representative suite of existing Variable Infiltration Capacity hydrologic model simulations driven by Coupled Model Intercomparison Project Phase 3 (CMIP3) climate simulations to train and evaluate a nonlinear and nonstationary extreme value model of annual extreme streamflow. The model was subsequently used to project changes under CMIP5-based climate change scenarios. Using this combination of process-based and statistical modeling, we project that the moderate (e.g., 2–20-year return period) extreme streamflow events will decrease in intensity. In contrast, projections of high intensity events (e.g., 100–200-year return period), which reflect complex interactions between temperature and precipitation changes, are inconclusive. The results provide a basis for developing a general understanding of the future streamflow extremes changes in nival basins and through careful consideration and adoption of appropriate covariates, the methodology could be employed for basins spanning a range of hydro-climatological regimes.



We acknowledge funding received for this project from the Flood Safety Section, Ministry of Forests Lands and Natural Resource Operations, B.C. Government. We thank three anonymous reviewers for comments towards an improved version of the manuscript.

Supplementary material

10584_2017_2098_MOESM1_ESM.pdf (2 mb)
ESM 1 (PDF 2.00 mb)


  1. Cannon AJ (2010) A flexible nonlinear modelling framework for nonstationary generalized extreme value analysis in hydroclimatology. Hydrol Process 24:673–685. CrossRefGoogle Scholar
  2. Cannon AJ (2014) GEVcdn: GEV conditional density estimation network. Accessed 22 Jan 2015
  3. Coles S (2001) An introduction to statistical modeling of extreme values. Springer Science & Business MediaGoogle Scholar
  4. Collins M, Knutti R, Arblaster J et al (2013) Long-term climate change: projections, commitments and irreversibility. In: Stocker T, Qin D, Plattner G et al (eds) Climate change 2013: the physical science basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, pp 1029–1136Google Scholar
  5. Cooley D (2013) Return periods and return levels under climate change. In: AghaKouchak A, Easterling D, Hsu K et al (eds) Extremes in a changing climate. Springer, Dordrecht, pp 97–114CrossRefGoogle Scholar
  6. Cubasch U, Wuebbles D, Chen D et al (2013) Introduction. In: Stocker TF, Qin D, Plattner G-K et al (eds) Climate change 2013: the physical science basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, pp 119–158Google Scholar
  7. Déry SJ, Hernández-Henríquez MA, Owens PN et al (2012) A century of hydrological variability and trends in the Fraser River basin. Environ Res Lett 7:024019. CrossRefGoogle Scholar
  8. Ebbwater Consulting (2015) Ebbwater Flood Map Project People living in BC floodplains. Accessed 16 Sep 2016
  9. Fraser Basin Council (2015) Flood and the Fraser. Accessed 24 Jul 2017
  10. Hirabayashi Y, Mahendran R, Koirala S et al (2013) Global flood risk under climate change. Nat Clim Chang 3:816–821. CrossRefGoogle Scholar
  11. Huntington TG (2006) Evidence for intensification of the global water cycle: review and synthesis. J Hydrol 319:83–95. CrossRefGoogle Scholar
  12. Jakob M, Church M (2011) The trouble with floods. Can Water Resour J Rev Can Ressour Hydr 36:287–292. CrossRefGoogle Scholar
  13. Jimenez Cisneros BE, Oki T, Arnell NW et al (2014) Freshwater resources. In: Field CB, Barros VR, Dokken DJ et al (eds) Climate change 2014: impacts, adaptation and vulnerability. Part A: global and sectoral aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, pp 229–269Google Scholar
  14. Kang DH, Gao H, Shi X et al (2016) Impacts of a rapidly declining mountain snowpack on streamflow timing in Canada’s Fraser River basin. Sci Rep 6:19299. CrossRefGoogle Scholar
  15. Katz RW (2013) Statistical methods for nonstationary extremes. In: AghaKouchak A, Easterling D, Hsu K et al (eds) Extremes in a changing climate. Springer, Dordrecht, pp 15–37CrossRefGoogle Scholar
  16. Katz RW, Parlange MB, Naveau P (2002) Statistics of extremes in hydrology. Adv Water Resour 25:1287–1304. CrossRefGoogle Scholar
  17. Kharin VV, Zwiers FW (2005) Estimating extremes in transient climate change simulations. J Clim 18:1156–1173. CrossRefGoogle Scholar
  18. Kharin VV, Zwiers FW, Zhang X, Wehner M (2013) Changes in temperature and precipitation extremes in the CMIP5 ensemble. Clim Chang.
  19. Kundzewicz ZW, Kanae S, Seneviratne SI et al (2013) Flood risk and climate change: global and regional perspectives. Hydrol Sci J 59:1–28. CrossRefGoogle Scholar
  20. Liang X, Lettenmaier DP, Wood EF, Burges SJ (1994) A simple hydrologically based model of land surface water and energy fluxes for general circulation models. J Geophys Res Atmospheres 99:14415–14428. CrossRefGoogle Scholar
  21. Liang X, Xie Z, Huang M (2003) A new parameterization for surface and groundwater interactions and its impact on water budgets with the variable infiltration capacity (VIC) land surface model. J Geophys Res Atmospheres 108:8613. CrossRefGoogle Scholar
  22. Maurer EP, Hidalgo HG (2008) Utility of daily vs. monthly large-scale climate data: an intercomparison of two statistical downscaling methods. Hydrol Earth Syst Sci 12:551–563CrossRefGoogle Scholar
  23. Meehl GA, Covey C, Delworth T et al (2007) The WCRP CMIP3 multimodel dataset—a new era in climate change research. Bull Am Meteorol Soc 88:1383–1394. CrossRefGoogle Scholar
  24. Milly P, Betancourt J, Falkenmark M et al (2008) Stationarity is dead: whither water management? Science 319:573–574. CrossRefGoogle Scholar
  25. Musselman KN, Clark MP, Liu C et al (2017) Slower snowmelt in a warmer world. Nat Clim Chang 7:214–219. CrossRefGoogle Scholar
  26. Northwest Hydraulic Consultants (2008) Comprehensive review of Fraser at Hope flood hydrology and flows—scoping study. Surrey, BCGoogle Scholar
  27. Northwest Hydraulic Consultants (2016) Regional assessment of flood vulnerability. North Vancouver, BCGoogle Scholar
  28. Panagoulia D, Economou P, Caroni C (2014) Stationary and nonstationary generalized extreme value modelling of extreme precipitation over a mountainous area under climate change. Environmetrics 25:29–43. CrossRefGoogle Scholar
  29. Public Safety Canada (2015) Floods. Accessed 14 Sep 2016
  30. Ramesh A (2013) Response of flood events to land use and climate change. Springer, DordrechtCrossRefGoogle Scholar
  31. Rootzén H, Katz RW (2013) Design life level: quantifying risk in a changing climate. Water Resour Res 49:5964–5972. CrossRefGoogle Scholar
  32. Salas J, Obeysekera J (2014) Revisiting the concepts of return period and risk for nonstationary hydrologic extreme events. J Hydrol Eng 19:554–568. CrossRefGoogle Scholar
  33. Sandink D, Kovacs P, Oulaheen G, McGillivray G (2010) Making floods insurable for Canadian homeowners: a discussion paper. Institute for Catastrophic Loss Reduction & Swiss Reinsurance Company Ltd., TorontoGoogle Scholar
  34. Schnorbus M, Bennett K, Werner A (2010) Quantifying the water resource impacts of mountain pine beetle and associated salvage harvest operations across a range of watershed scales: hydrologic modeling of the Fraser River basin. Canadian Forest Service PublicationsGoogle Scholar
  35. Schnorbus MA, Cannon AJ (2014) Statistical emulation of streamflow projections from a distributed hydrological model: application to CMIP3 and CMIP5 climate projections for British Columbia, Canada. Water Resour Res n/a-n/a.
  36. Serinaldi F, Kilsby CG (2015) Stationarity is undead: uncertainty dominates the distribution of extremes. Adv Water Resour 77:17–36. CrossRefGoogle Scholar
  37. Shrestha RR, Schnorbus MA, Peters DL (2016) Assessment of a hydrologic model’s reliability in simulating flow regime alterations in a changing climate. Hydrol Process 30:2628–2643. CrossRefGoogle Scholar
  38. Shrestha RR, Schnorbus MA, Werner AT, Berland AJ (2012) Modelling spatial and temporal variability of hydrologic impacts of climate change in the Fraser River basin, British Columbia, Canada. Hydrol Process 26:1840–1860. CrossRefGoogle Scholar
  39. Simm J, Wallis M, Smith P et al (2012) The significance of failure modes in the design and management of levees—a perspective from the International Levee handbook team. In: Proceedings of the 2nd European Conference on Flood Risk Management. CRC Press, Rotterdam, pp 1–15Google Scholar
  40. Taylor KE, Stouffer RJ, Meehl GA (2012) An overview of CMIP5 and the experiment design. Bull Am Meteorol Soc 93:485–498. CrossRefGoogle Scholar
  41. Towler E, Rajagopalan B, Gilleland E et al (2010) Modeling hydrologic and water quality extremes in a changing climate: a statistical approach based on extreme value theory. Water Resour Res 46:W11504. Google Scholar
  42. Vasiliades L, Galiatsatou P, Loukas A (2014) Nonstationary frequency analysis of annual maximum rainfall using climate covariates. Water Resour Manag 29:339–358. CrossRefGoogle Scholar
  43. Wood A, Leung L, Sridhar V, Lettenmaier D (2004) Hydrologic implications of dynamical and statistical approaches to downscaling climate model outputs. Clim Chang 62:189–216CrossRefGoogle Scholar
  44. Zhang X, Wang J, Zwiers FW, Groisman PY (2010) The influence of large-scale climate variability on winter maximum daily precipitation over North America. J Clim 23:2902–2915. CrossRefGoogle Scholar

Copyright information

© Her Majesty the Queen in Right of Canada 2017

Authors and Affiliations

  • Rajesh R. Shrestha
    • 1
    • 2
    Email author
  • Alex J. Cannon
    • 3
  • Markus A. Schnorbus
    • 2
  • Francis W. Zwiers
    • 2
  1. 1.Watershed Hydrology and Ecology Research Division, Environment and Climate Change CanadaUniversity of VictoriaVictoriaCanada
  2. 2.Pacific Climate Impacts ConsortiumUniversity of VictoriaVictoriaCanada
  3. 3.Climate Research Division, Environment and Climate Change CanadaUniversity of VictoriaVictoriaCanada

Personalised recommendations