Uncertainty in hydrological signatures for gauged and ungauged catchments

Ida K Westerberg*, Thorsten Wagener, Gemma Coxon, Hilary K. Mcmillan, Attilio Castellarin, Alberto Montanari, Jim Freer

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

107 Citations (Scopus)
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Reliable information about hydrological behavior is needed for water-resource management and scientific investigations. Hydrological signatures quantify catchment behavior as index values, and can be predicted for ungauged catchments using a regionalization procedure. The prediction reliability is affected by data uncertainties for the gauged catchments used in prediction and by uncertainties in the regionalization procedure. We quantified signature uncertainty stemming from discharge data uncertainty for 43 UK catchments and propagated these uncertainties in signature regionalization, while accounting for regionalization uncertainty with a weighted-pooling-group approach. Discharge uncertainty was estimated using Monte Carlo sampling of multiple feasible rating curves. For each sampled rating curve, a discharge time series was calculated and used in deriving the gauged signature uncertainty distribution. We found that the gauged uncertainty varied with signature type, local measurement conditions and catchment behavior, with the highest uncertainties (median relative uncertainty ±30-40% across all catchments) for signatures measuring high- and low-flow magnitude and dynamics. Our regionalization method allowed assessing the role and relative magnitudes of the gauged and regionalized uncertainty sources in shaping the signature uncertainty distributions predicted for catchments treated as ungauged. We found that (1) if the gauged uncertainties were neglected there was a clear risk of overconditioning the regionalization inference, e.g., by attributing catchment differences resulting from gauged uncertainty to differences in catchment behavior, and (2) uncertainty in the regionalization results was lower for signatures measuring flow distribution (e.g., mean flow) than flow dynamics (e.g., autocorrelation), and for average flows (and then high flows) compared to low flows.

Original languageEnglish
Pages (from-to)1847-1865
Number of pages19
JournalWater Resources Research
Issue number3
Early online date2 Feb 2016
Publication statusPublished - Mar 2016

Structured keywords

  • Water and Environmental Engineering


  • Discharge uncertainty
  • Eco-hydrological flow indices
  • Hydrological signatures
  • Rating curve
  • Regionalization
  • Ungauged basins


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