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

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

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. Copyright Springer Science+Business Media Dordrecht 2014

Suggested Citation

  • Jean-François Exbrayat & Wouter Buytaert & Edison Timbe & David Windhorst & Lutz Breuer, 2014. "Addressing sources of uncertainty in runoff projections for a data scarce catchment in the Ecuadorian Andes," Climatic Change, Springer, vol. 125(2), pages 221-235, July.
  • Handle: RePEc:spr:climat:v:125:y:2014:i:2:p:221-235
    DOI: 10.1007/s10584-014-1160-x
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    References listed on IDEAS

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    1. Walter Immerzeel & L. Beek & M. Konz & A. Shrestha & M. Bierkens, 2012. "Hydrological response to climate change in a glacierized catchment in the Himalayas," Climatic Change, Springer, vol. 110(3), pages 721-736, February.
    2. Plesca, I. & Timbe, E. & Exbrayat, J.-F. & Windhorst, D. & Kraft, P. & Crespo, P. & Vaché, K.B. & Frede, H.-G. & Breuer, L., 2012. "Model intercomparison to explore catchment functioning: Results from a remote montane tropical rainforest," Ecological Modelling, Elsevier, vol. 239(C), pages 3-13.
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    1. A. Chamorro & P. Kraft & G. Pauer & J.-F. Exbrayat & L. Breuer, 2017. "Effect of (quasi-)optimum model parameter sets and model characteristics on future discharge projection of two basins from Europe and Asia," Climatic Change, Springer, vol. 142(3), pages 559-573, June.

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