Articles | Volume 19, issue 4
https://doi.org/10.5194/hess-19-1615-2015
https://doi.org/10.5194/hess-19-1615-2015
Research article
 | 
08 Apr 2015
Research article |  | 08 Apr 2015

Approximating uncertainty of annual runoff and reservoir yield using stochastic replicates of global climate model data

M. C. Peel, R. Srikanthan, T. A. McMahon, and D. J. Karoly

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Short summary
We present a proof-of-concept approximation of within-GCM uncertainty using non-stationary stochastic replicates of monthly precipitation and temperature projections and investigate the impact of within-GCM uncertainty on projected runoff and reservoir yield. Amplification of within-GCM variability from precipitation to runoff to reservoir yield suggests climate change impact assessments ignoring within-GCM uncertainty would provide water resources managers with an unjustified sense of certainty