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Assessment of a lumped coupled flow‐isotope model in data scarce Boreal catchments
Author(s) -
Smith A.,
Welch C.,
Stadnyk T.
Publication year - 2016
Publication title -
hydrological processes
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.222
H-Index - 161
eISSN - 1099-1085
pISSN - 0885-6087
DOI - 10.1002/hyp.10835
Subject(s) - streamflow , environmental science , hydrology (agriculture) , precipitation , wetland , groundwater , boreal , drainage basin , flood forecasting , geology , ecology , geography , meteorology , paleontology , cartography , geotechnical engineering , biology
Quantifying streamflow sources within remote, data scarce, Boreal catchments remains a significant challenge because of 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. Copyright © 2016 John Wiley & Sons, Ltd.