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Using Isotopes to Constrain Water Flux and Age Estimates in Snow

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Using Isotopes to Constrain Water Flux and Age Estimates in Snow Hydrol. Earth Syst. Sci., 21, 5089–5110, 2017 https://doi.org/10.5194/hess-21-5089-2017 © Author(s) 2017. This work is distributed under the Creative Commons Attribution 3.0 License. Using isotopes to constrain water flux and age estimates in snow-influenced catchments using the STARR (Spatially distributed Tracer-Aided Rainfall–Runoff) model Pertti Ala-aho1, Doerthe Tetzlaff1, James P. McNamara2, Hjalmar Laudon3, and Chris Soulsby1 1Northern Rivers Institute, School of Geosciences, University of Aberdeen, AB24 3UF, UK 2Department of Geosciences, Boise State University, Boise, ID 83725, USA 3Department of Forest, Ecology and Management, Swedish University of Agricultural Sciences, 90183 Umeå, Sweden Correspondence to: Pertti Ala-aho ([email protected]) Received: 24 February 2017 – Discussion started: 9 March 2017 Revised: 28 June 2017 – Accepted: 18 August 2017 – Published: 9 October 2017 Abstract. Tracer-aided hydrological models are increasingly water age distributions, which was captured by the model. used to reveal fundamentals of runoff generation processes Our study suggested that snow sublimation fractionation pro- and water travel times in catchments. Modelling studies in- cesses can be important to include in tracer-aided modelling tegrating stable water isotopes as tracers are mostly based for catchments with seasonal snowpack, while the influence in temperate and warm climates, leaving catchments with of fractionation during snowmelt could not be unequivocally strong snow influences underrepresented in the literature. shown. Our work showed the utility of isotopes to provide Such catchments are challenging, as the isotopic tracer sig- a proof of concept for our modelling framework in snow- nals in water entering the catchments as snowmelt are typi- influenced catchments. cally distorted from incoming precipitation due to fractiona- tion processes in seasonal snowpack. We used the Spatially distributed Tracer-Aided Rainfall– 1 Introduction Runoff (STARR) model to simulate fluxes, storage, and mix- ing of water and tracers, as well as estimating water ages Tracer-aided hydrological models provide invaluable in- in three long-term experimental catchments with varying de- sights into how water and solutes are partitioned, stored, grees of snow influence and contrasting landscape character- and transported within catchments (Seibert and McDonnell, istics. In the context of northern catchments the sites have 2002; Kirchner, 2006). They can also be used to explore met- exceptionally long and rich data sets of hydrometric data and rics of catchment hydrological function such as water age – most importantly – stable water isotopes for both rain and and travel times, leading to new avenues for use in study- snow conditions. To adapt the STARR model for sites with ing ecohydrological water partitioning and anthropogenic in- strong snow influence, we used a novel parsimonious calcu- fluences (Birkel and Soulsby, 2015). Snow-influenced catch- lation scheme that takes into account the isotopic fractiona- ments, particularly in the Northern Hemisphere, have a long tion through snow sublimation and snowmelt. history in hydrological modelling with the ultimate goal of The modified STARR setup simulated the streamflows, reproducing the stream hydrograph where spring snowmelt isotope ratios, and snow pack dynamics quite well in all plays a dominant role (Hinzman and Kane, 1991; Seibert, three catchments. From this, our simulations indicated con- 1999; Pomeroy et al., 2007). An essential part of this is cor- trasting median water ages and water age distributions be- rectly representing snow accumulation and melt, and impor- tween catchments brought about mainly by differences in tantly its spatial distribution, and as a result numerous tools topography and soil characteristics. However, the variable of variable complexity have emerged to simulate catchment- degree of snow influence in catchments also had a major scale snow processes (Tarboton and Luce, 1996; Lehning et influence on the stream hydrograph, storage dynamics, and al., 2002; Liston and Elder, 2006). However, using tracer- Published by Copernicus Publications on behalf of the European Geosciences Union. 5090 P. Ala-aho et al.: Using isotopes to constrain water flux and age estimates aided models in these regions has been less common (Tetzlaff challenge, the Spatially distributed Trace-Aided Rainfall– et al., 2015b) – mainly due to difficulties of routine, long- Runoff (STARR) model was developed to fully distribute the term field work, and sample collection in such cold and of- simulation for hydrological storages, fluxes, isotope ratios ten remote regions. Nevertheless, environmental tracers have and water age in the landscape (Huijgevoort et al., 2016a, b). been used at some sites to increase conceptual process un- This follows on from previous conceptual models that have derstanding in the field and for hydrograph separation stud- used spatially explicit frameworks for tracking isotopes in ies (Sklash and Farvolden, 1979; Laudon et al., 2002; Carey the rainfall–runoff transformation (Sayama and McDonnell, and Quinton, 2004; Schmieder et al., 2016). 2009). The STARR model was originally developed for a Stable water isotopes oxygen-18 and deuterium are com- long-term experimental catchment in the Scottish Highlands, monly used environmental tracers because of their conserva- the Bruntland Burn, with the aim to keep the model simple to tive properties and automatic entry to natural systems with be applicable as a generic tool across northern regions with precipitation (Birkel and Soulsby, 2015). They are also in- strong snowmelt influence (Tetzlaff et al., 2015a). creasingly easy and inexpensive to analyse in large num- In this study, we apply the STARR model in three well- bers (Berman et al., 2009). In snow-influenced environments, established research catchments with long and frequent data the cryogenic processes complicate the isotope input signal sets of stable water isotopes (Tetzlaff et al., 2017). All exper- through several processes. Firstly during snow accumulation imental catchments experience seasonal snow influence, but snowfalls with different isotopic composition make up the are contrasting in their topography, dominant soil types, and snowpack with distinct isotopic layers typically persisting canopy cover. The main advancement of the STARR model until the wholesale snowmelt (Rodhe, 1981), though a degree reported here is replacing the original degree-day snow of internal isotopic redistribution is typically present in the module with an energy-driven process-based snow module snowpack (Taylor et al., 2001; Evans et al., 2016). Internal that can track isotopes (Ala-aho et al., 2017b). The novel mixing processes do not considerably influence the bulk iso- snow module encompasses original algorithms to account for topic composition of the snowpack, but fractionation due to (1) sublimation fractionation of snow isotopes of canopy in- snow sublimation has the potential to isotopically enrich the tercepted snow and ground snowpack and (2) time-variant snowpack in relation to snowfall (Moser and Stichler, 1974; depletion of the snowmelt. Both processes are well docu- Earman et al., 2006). Furthermore, canopy snow interception mented in laboratory, field, and modelling studies (Cooper et can provide an additional transient storage subjected to sub- al., 1993; Claassen and Downey, 1995; Taylor et al., 2001; limation, and thereby fractionation processes, further ampli- Laudon et al., 2002, see e.g. Carey and Quinton, 2004; fying the snow isotopic enrichment (Claassen and Downey, Koeniger et al., 2008; Schmieder et al., 2016), but have not 1995; Koeniger et al., 2008). Finally, several field, labora- before been incorporated to tracer-aided modelling in a spa- tory, and modelling studies (Shanley et al., 1995; Taylor et tially explicit manner. al., 2001; Feng et al., 2002) demonstrate how the onset of The overarching goal for this study is to better under- snowmelt tends to be depleted in heavy isotopes in compari- stand spatial distribution and non-stationary responses of wa- son to average snowpack, and the snowpack isotopically en- ter ages in snow-influenced northern catchments. We achieve riches over the course of snowmelt. This “melt-out” process, this by using the STARR model to simulate spatially dis- though a complex and variable phenomenon in field condi- tributed flows, isotopes, and snow water equivalent (SWE) tions, has been shown by, for example, Taylor et al. (2002) in three long-term experimental catchments. The contrast- to be rather a rule than exception for snowmelt of seasonal ing catchment characteristics make a strong test for the snowpacks in various climates. As a combined results of the model adaptability in different cold climate conditions. As processes above, water entering the catchment as liquid is not a novel aspect, we test new empirical parsimonious routines only delayed in timing because of being stored as snow but for stable water isotope processes in seasonal snowpacks in is typically also altered in its isotopic composition (Laudon our catchment-scale simulations. A wider importance of our et al., 2002; Schmieder et al., 2016). In most environments work is in advancing tools for process understanding and such processes have a high degree of spatial variability and management of snow-influenced environments that are un- are thus challenging to model at the catchment scale. derrepresented in research but are on the verge of drastic Historically,
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