The importance of snowmelt spatiotemporal variability for isotope-based hydrograph separation in a high-elevation catchment

Abstract

Abstract. Seasonal snow cover is an important temporary water storage in high-elevation regions. Especially in remote areas, the available data are often insufficient to accurately quantify snowmelt contributions to streamflow. The limited knowledge about the spatiotemporal variability of the snowmelt isotopic composition, as well as pronounced spatial variation in snowmelt rates, leads to high uncertainties in applying the isotope-based hydrograph separation method. The stable isotopic signatures of snowmelt water samples collected during two spring 2014 snowmelt events at a north-and a south-facing slope were volume weighted with snowmelt rates derived from a distributed physicsbased snow model in order to transfer the measured plotscale isotopic composition of snowmelt to the catchment scale. The observed δ 18 O values and modeled snowmelt rates showed distinct inter-and intra-event variations, as well as marked differences between north-and south-facing slopes. Accounting for these differences, two-component isotopic hydrograph separation revealed snowmelt contributions to streamflow of 35 ± 3 and 75 ± 14 % for the early and peak melt season, respectively. These values differed from those determined by formerly used weighting methods (e.g., using observed plot-scale melt rates) or considering either the north-or south-facing slope by up to 5 and 15 %, respectively.

Using isotopes to constrain water flux and age estimates in snow-influenced catchments using the STARR (Spatially distributed Tracer-Aided Rainfall–Runoff) model

“…Both processes are well documented in laboratory, field, and modelling studies (Cooper et al, 1993;Claassen and Downey, 1995;Taylor et al, 2001;Laudon et al, 2002, see e.g. Carey and Quinton, 2004;Koeniger et al, 2008;Schmieder et al, 2016), but have not before been incorporated to tracer-aided modelling in a spatially explicit manner.…”

“…This "melt-out" process, though a complex and variable phenomenon in field conditions, has been shown by, for example, Taylor et al (2002) to be rather a rule than exception for snowmelt of seasonal snowpacks in various climates. As a combined results of the processes above, water entering the catchment as liquid is not only delayed in timing because of being stored as snow but is typically also altered in its isotopic composition (Laudon et al, 2002;Schmieder et al, 2016). In most environments such processes have a high degree of spatial variability and are thus challenging to model at the catchment scale.…”

“…However, using tracer-aided models in these regions has been less common -mainly due to difficulties of routine, longterm field work, and sample collection in such cold and often remote regions. Nevertheless, environmental tracers have been used at some sites to increase conceptual process understanding in the field and for hydrograph separation studies (Sklash and Farvolden, 1979;Laudon et al, 2002;Carey and Quinton, 2004;Schmieder et al, 2016).…”

Lessons learned from monitoring the stable water isotopic variability in precipitation and streamflow across a snow-dominated subarctic catchment

“…Fractionation in the phase changes of sublimation/condensation and freeze/thaw during percolation through snow (O'Neil 1968) has the potential to change the isotopic signal in the original precipitation. The isotopic variability observed in the snowpack is usually marked both vertically in the profile, because of the persistence of isotopically different snowfall (Evans et al 2016;Moser and Stichler 1974), and at various locations in the landscape (Dahlke and Lyon 2013;Schmieder et al 2016).…”

Using Isotopic and Geochemical Tracers to Determine the Contribution of Glacier‐Snow Meltwater to Streamflow in a Partly Glacierized Alpine‐Gorge Catchment in Northeastern Qinghai‐Tibet Plateau

“…As an elevation effect exists in the δ 18 O values (Gonfiantini et al, ), elevation‐weighted mean rainwater δ 18 O value was used in the hydrograph separation. The elevation‐weighted mean rainwater δ 18 O and its standard deviation were calculated using the following equations (Alaaho et al, ; Schmieder et al, ): where C r 18O and σ are the elevation‐weighted mean rainwater δ 18 O value and its standard deviation, respectively; C j is the measured δ 18 O value of rainwater at the observation site j ; P j is the measured amount of rainfall at the observation site j , and A j is the area represented by the observation site j and defined as the horizontally projected area between two contour lines that go through the observation sites j and j + 1 (For the site 7, it is all area above 4,160 m asl).…”