Assessment of a lumped coupled flow-isotope model in data scarce Boreal catchments

A. Smith, C. Welch, T. Stadnyk

Research output: Contribution to journalArticlepeer-review

22 Citations (Scopus)


Quantifying streamflow sources within remote, data scarce, Boreal catchments remains a significant challenge due to limited accessibility and complex, flat topography. The coupled use of hydrometric and isotopic data has previously been shown to facilitate quantification of streamflow sources, but application has generally been limited to small basins and short time scales. A lumped flow-isotope model was used to estimate contributing streamflow sources (soil, ground, and wetland water) over a four year period in two large nested headwater catchments (Sapochi and Odei Rivers) in northern Manitoba, Canada. On average, the primary streamflow source was estimated as soil water (60%) in the Sapochi River, and groundwater (54%) in the Odei River. A strong seasonal influence was observed: soil water was the primary streamflow source in summer, changing to groundwater and wetlands during the winter. Interannual variability in streamflow sources was strongly linked to the presence or absence of late summer rainfall. The greatest uncertainties in source quantification were identified during the spring freshets and high precipitation events, and hence, simulations may be improved through explicit representation of the soil freeze/thaw process and data collection during this period. Assessment of primary streamflow components and qualitative uncertainty estimation using coupled isotope-flow modelling is an effective method for first order identification of streamflow sources in data sparse remote headwaters. This article is protected by copyright. All rights reserved.
Original languageEnglish
Pages (from-to)3871-3884
Number of pages14
JournalHydrological Processes
Issue number21
Early online date21 Jun 2016
Publication statusPublished - 15 Oct 2016


  • isotope modelling
  • stable water isotopes
  • Nelson River
  • Canada
  • sparsely gauged basins
  • Boreal


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