scholarly journals Supplementary material to "The importance of spatio-temporal snowmelt variability for isotopic hydrograph separation in a high-elevation catchment"

Author(s):  
Jan Schmieder ◽  
Florian Hanzer ◽  
Thomas Marke ◽  
Jakob Garvelmann ◽  
Michael Warscher ◽  
...  
2016 ◽  
Author(s):  
Jan Schmieder ◽  
Florian Hanzer ◽  
Thomas Marke ◽  
Jakob Garvelmann ◽  
Michael Warscher ◽  
...  

Abstract. Seasonal snow cover is an important temporary water storage in high-elevation regions. Especially in remote areas, the available data is often insufficient to explicitly quantify snowmelt contributions to streamflow. The unknown spatio-temporal variability of the snowmelt isotopic content, as well as pronounced spatial variations of snowmelt rates lead to high uncertainties in applying the isotopic hydrograph separation method. This study presents an approach that uses a distributed snowmelt model to support the traditional isotopic hydrograph separation technique. 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 physics-based snow model in order to transfer the measured plot-scale isotopic content of snowmelt water to the catchment scale. The observed δ18O values and modelled snowmelt rates showed distinct inter- and intra-event variations, as well as marked differences between north- and south-facing slopes. Accounting for those differences, two-component isotopic hydrograph separation revealed snowmelt contributions of 35 ± 3 % and 75 ± 14 % for the early and peak melt season, respectively. Differences to formerly used weighting methods (e.g. using observed plot-scale melt rates) or considering either the north- or south-facing slope were up to 5 and 15 %, respectively.


2021 ◽  
Author(s):  
Emilija Krsnik ◽  
Katharina Methner ◽  
Marion Campani ◽  
Svetlana Botsyun ◽  
Sebastian G. Mutz ◽  
...  

2019 ◽  
Author(s):  
Giovanni Denaro ◽  
Daniela Salvagio Manta ◽  
Alessandro Borri ◽  
Maria Bonsignore ◽  
Davide Valenti ◽  
...  

Author(s):  
Guilherme E. H. Nogueira ◽  
Christian Schmidt ◽  
Daniel Partington ◽  
Philip Brunner ◽  
Jan H. Fleckenstein

Author(s):  
Odiney Alvarez-Campos ◽  
Elizabeth J. Olson ◽  
Marty D. Frisbee ◽  
Sebastián A. Zuñiga Medina ◽  
José Díaz Rodríguez ◽  
...  

2020 ◽  
Author(s):  
Michael McCarthy ◽  
Flavia Burger ◽  
Alvaro Ayala ◽  
Stefan Fugger ◽  
Thomas E Shaw ◽  
...  

<p>The Andean cryosphere is a vital water resource for downstream populations. In recent years, it has been in steep decline as a whole, but shown strong spatio-temporal variability due to climatic events such as the current mega drought in central Chile. Glacio-hydrological models are necessary to understand and predict changes in water availability as a result of changes to the cryosphere. However, due to a lack of data for initialisation, forcing, calibration and validation, they are rarely used, especially in the Andes, for periods longer than a few years or decades. While useful insights can be gained from short-term modelling, there is a gap in our understanding of how glaciers impact hydrology on longer timescales, which may prevent local communities and governments from achieving effective planning and mitigation. Here we use the glacio-hydrological model TOPKAPI-ETH – initialised, forced, calibrated and validated using unique and extensive field and remote sensing datasets – to investigate glacier contributions to the streamflow of the high-elevation Rio Yeso catchment, Chile, over the past 50 years. We focus in particular on: 1) fluctuations in glacier surface mass balance and runoff and associated climatic variability; 2) if peak water has already occurred and when; 3) the effect of supraglacial debris cover on seasonal and long-term hydrographs. We offer insights into some of the challenges of running glacio-hydrological models on longer timescales and discuss the implications of our findings in the context of a shrinking Andean cryosphere.</p>


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