Acknowledgements. This work was funded by the NERC/JPI SIWA project (NE/M019896/1) and the European Research Council ERC (project GA 335910 VeWa). Numerical simulations were performed using the Maxwell High Performance Computing Cluster of the University of Aberdeen IT Service, provided by Dell Inc. and supported by Alces Software. The isotope work in Krycklan is funded by the KAW Branch-Point project together with SKB and SITES. We would like to thank Marjolein van Hui- jgevoort for her help with the STARR code, and Masaki Hayashi and two anonymous reviewers for their insightful suggestions that significantly improved the paper. The Supplement related to this article is available online at https://doi.org/10.5194/hess-21-5089-2017-supplement.Peer reviewedPublisher PD

Ala-aho, Pertti

Laudon, Hjalmar

McNamara, James P.

Soulsby, Chris

Tetzlaff, Doerthe

English

Tracer-aided hydrological models are increasingly used to reveal fundamentals of runoff generation processes and water travel times in catchments. Modelling studies integrating stable water isotopes as tracers are mostly based in temperate and warm climates, leaving catchments with strong snow influences underrepresented in the literature. Such catchments are challenging, as the isotopic tracer signals in water entering the catchments as snowmelt are typically distorted from incoming precipitation due to fractionation processes in seasonal snowpack.
We used the Spatially distributed Tracer-Aided Rainfall– Runoff (STARR) model to simulate fluxes, storage, and mixing of water and tracers, as well as estimating water ages in three long-term experimental catchments with varying degrees of snow influence and contrasting landscape characteristics. In the context of northern catchments the sites have exceptionally long and rich data sets of hydrometric data and – most importantly – stable water isotopes for both rain and snow conditions. To adapt the STARR model for sites with strong snow influence, we used a novel parsimonious calculation scheme that takes into account the isotopic fractionation through snow sublimation and snowmelt.
The modified STARR setup simulated the streamflows, isotope ratios, and snow pack dynamics quite well in all three catchments. From this, our simulations indicated contrasting median water ages and water age distributions between catchments brought about mainly by differences in topography and soil characteristics. However, the variable degree of snow influence in catchments also had a major influence on the stream hydrograph, storage dynamics, and water age distributions, which was captured by the model. Our study suggested that snow sublimation fractionation processes can be important to include in tracer-aided modelling for catchments with seasonal snowpack, while the influence of fractionation during snowmelt could not be unequivocally shown. Our work showed the utility of isotopes to provide a proof of concept for our modelling framework in snow-influenced catchments

Ala-Aho, Pertti

Boise State University - ScholarWorks

Using Isotopes to Constrain Water Flux and Age Estimates in Snow-Influenced Catchments Using the STARR (Spatially Distributed Tracer-Aided Rainfall–Runoff) Model

Tracer-aided hydrological models are increasingly used to reveal fundamentals

of runoff generation processes and water travel times in catchments.

Modelling studies integrating stable water isotopes as tracers are mostly

based in temperate and warm climates, leaving catchments with strong snow

influences underrepresented in the literature. Such catchments are

challenging, as the isotopic tracer signals in water entering the catchments

as snowmelt are typically distorted from incoming precipitation due to

fractionation processes in seasonal snowpack.



We used the  Spatially distributed

Tracer-Aided Rainfall–Runoff (STARR) model

to simulate fluxes, storage, and mixing of water and tracers, as well

as estimating water ages in three long-term experimental catchments with

varying degrees of snow influence and contrasting landscape characteristics.

In the context of northern catchments the sites have exceptionally long and

rich data sets of hydrometric data and – most importantly – stable water

isotopes for both rain and snow conditions. To adapt the STARR model for

sites with strong snow influence, we used a novel parsimonious calculation

scheme that takes into account the isotopic fractionation through snow

sublimation and snowmelt.



The modified STARR setup simulated the streamflows, isotope ratios, and snow

pack dynamics quite well in all three catchments. From this, our simulations

indicated contrasting median water ages and water age distributions between

catchments brought about mainly by differences in topography and soil

characteristics. However, the variable degree of snow influence in

catchments also had a major influence on the stream hydrograph, storage

dynamics, and water age distributions, which was captured by the model. Our

study suggested that snow sublimation fractionation processes can be

important to include in tracer-aided modelling for catchments with seasonal

snowpack, while the influence of fractionation during snowmelt could not be

unequivocally shown. Our work showed the utility of isotopes to provide a

proof of concept for our modelling framework in snow-influenced catchments

P. Ala-aho

D. Tetzlaff

J. P. McNamara

H. Laudon

C. Soulsby

Directory of Open Access Journals

Hydrology and Earth System Sciences

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

Research Archive

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

https://aura.abdn.ac.uk/bitstream/2164/9528/1/hess_21_5089_2017.pdf

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

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Boise State University - ScholarWorks

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