EGU24-16018, updated on 09 Mar 2024
https://doi.org/10.5194/egusphere-egu24-16018
EGU General Assembly 2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Understanding snow meltwater fractional contributions to streamflow in a subarctic catchment

Pertti Ala-aho1, Kashif Noor1, Jeffrey M. Welker2,3,4, Kaisa-Riikka Mustonen2, Björn Klöve1, and Hannu Marttila1
Pertti Ala-aho et al.
  • 1Water, Energy and Environmental Engineering Research Unit, University of Oulu, Oulu, Finland
  • 2Ecology and Genetics Research Unit, University of Oulu, Oulu, Finland
  • 3University of Alaska Anchorage, Anchorage, Alaska, USA
  • 4University of the Arctic-UArctic, Rovaniemi, Finland

Snow plays an important role in the Northern water cycle providing temporary water storage, and resulting in high flows during spring snowmelt. Snow is experiencing rapid changes due to global warming, and process-based understanding of how snowmelt interacts with the environment is becoming ever more important. Stable isotopes of 18O and 2H are recognized as reliable tracers for determining water sources and tracing their movement within a catchment. The Isotope-Based Hydrograph Separation (IHS) is used to determine the mix of water sources in streams. However, when determining the snowmelts contribution to streamflow using IHS, uncertainties arise due to the lack of a clear and consistent snow sampling approach do define the isotope signal of snowmelt water for IHS calculations. To tackle these uncertainties, we did intensive sampling of snowfall, snowpack, and snow meltwater 18O isotopes at the Pallas catchment in Northern Finland. Our examination of different snow sampling strategies revealed potential biases in the IHS analysis. By employing samples directly from the snowmelt water 18O isotope value as an endmember in IHS, we determined the fractional contribution from streamflow was 59.6% (with a ±2% uncertainty). Yet, using alternate average weighted isotope values from either snowfall or mid-winter snowpack resulted in underestimations of snowmelt fraction by 17.8% and 22.6% respectively. In the absence of snowmelt samples, samples collected from the snowpack during high snowmelt period resulted in smaller biases (4.2 % lower snowmelt fractions). Our findings underline the importance of selecting the right snow sampling method for IHS, or any other ecohydrological analysis using stable water isotope tracers.

How to cite: Ala-aho, P., Noor, K., Welker, J. M., Mustonen, K.-R., Klöve, B., and Marttila, H.: Understanding snow meltwater fractional contributions to streamflow in a subarctic catchment, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16018, https://doi.org/10.5194/egusphere-egu24-16018, 2024.