Climatic Change

, Volume 125, Issue 2, pp 221–235

Addressing sources of uncertainty in runoff projections for a data scarce catchment in the Ecuadorian Andes

  • Jean-François Exbrayat
  • Wouter Buytaert
  • Edison Timbe
  • David Windhorst
  • Lutz Breuer
Article

DOI: 10.1007/s10584-014-1160-x

Cite this article as:
Exbrayat, JF., Buytaert, W., Timbe, E. et al. Climatic Change (2014) 125: 221. doi:10.1007/s10584-014-1160-x

Abstract

Future climate projections from general circulation models (GCMs) predict an acceleration of the global hydrological cycle throughout the 21st century in response to human-induced rise in temperatures. However, projections of GCMs are too coarse in resolution to be used in local studies of climate change impacts. To cope with this problem, downscaling methods have been developed that transform climate projections into high resolution datasets to drive impact models such as rainfall-runoff models. Generally, the range of changes simulated by different GCMs is considered to be the major source of variability in the results of such studies. However, the cascade of uncertainty in runoff projections is further elongated by differences between impact models, especially where robust calibration is hampered by the scarcity of data.

Here, we address the relative importance of these different sources of uncertainty in a poorly monitored headwater catchment of the Ecuadorian Andes. Therefore, we force 7 hydrological models with downscaled outputs of 8 GCMs driven by the A1B and A2 emission scenarios over the 21st century. Results indicate a likely increase in annual runoff by 2100 with a large variability between the different combinations of a climate model with a hydrological model. Differences between GCM projections introduce a gradually increasing relative uncertainty throughout the 21st century. Meanwhile, structural differences between applied hydrological models still contribute to a third of the total uncertainty in late 21st century runoff projections and differences between the two emission scenarios are marginal.

Supplementary material

10584_2014_1160_MOESM1_ESM.pdf (373 kb)
ESM 1(PDF 373 kb)

Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  • Jean-François Exbrayat
    • 1
    • 2
  • Wouter Buytaert
    • 3
  • Edison Timbe
    • 4
    • 5
  • David Windhorst
    • 4
  • Lutz Breuer
    • 4
  1. 1.School of GeoSciences and National Centre for Earth ObservationUniversity of EdinburghEdinburghUK
  2. 2.Climate Change Research Centre and ARC Centre of Excellence for Climate System ScienceUniversity of New South WalesSydneyAustralia
  3. 3.Civil and Environmental Engineering & Grantham Institute for Climate Change, Imperial College LondonLondonUK
  4. 4.Institute for Landscape Ecology and Resources Management (ILR), Research Centre for BioSystems, Land Use and Nutrition (IFZ)Justus-Liebig-Universität GießenGießenGermany
  5. 5.Grupo de Ciencias de la Tierra y del Ambiente, DIUCUniversidad de CuencaCuencaEcuador

Personalised recommendations