Comparing Bayesian and traditional end-member mixing approaches for hydrograph separation in a glacierized basin

<p>Tracer data have been successfully used for hydrograph separation in glacierized basins. However, in these basins uncertainties of the hydrograph separation are large and are caused by the spatiotemporal variability in the tracer signatures of water sources, the uncertainty of water samplin...

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Main Authors: Z. He, K. Unger-Shayesteh, S. Vorogushyn, S. M. Weise, D. Duethmann, O. Kalashnikova, A. Gafurov, B. Merz
Format: Article
Language:English
Published: Copernicus Publications 2020-06-01
Series:Hydrology and Earth System Sciences
Online Access:https://www.hydrol-earth-syst-sci.net/24/3289/2020/hess-24-3289-2020.pdf
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spelling doaj-6d4585e9e32448bd960fea6f3a4f94952020-11-25T02:47:51ZengCopernicus PublicationsHydrology and Earth System Sciences1027-56061607-79382020-06-01243289330910.5194/hess-24-3289-2020Comparing Bayesian and traditional end-member mixing approaches for hydrograph separation in a glacierized basinZ. He0Z. He1K. Unger-Shayesteh2S. Vorogushyn3S. M. Weise4D. Duethmann5D. Duethmann6O. Kalashnikova7A. Gafurov8B. Merz9B. Merz10Hydrology Section, GFZ German Research Centre for Geosciences, Telegrafenberg, Potsdam, Germanynow at: Center for Hydrology, University of Saskatchewan, Saskatoon, Saskatchewan, CanadaInternational Relations, German Aerospace Center (DLR), Linder Höhe, Cologne, GermanyHydrology Section, GFZ German Research Centre for Geosciences, Telegrafenberg, Potsdam, GermanyDepartment of Catchment Hydrology, Helmholtz Centre for Environmental Research (UFZ), Halle, GermanyInstitute of Hydraulic Engineering and Water Resources Management, Vienna University of Technology (TU Wien), Vienna, AustriaDepartment of Ecohydrology, Leibniz-Institute of Freshwater Ecology and Inland Fisheries (IGB), Berlin, GermanyClimate, Water and Natural Resources Department, Central Asian Institute for Applied Geosciences (CAIAG), Bishkek, KyrgyzstanHydrology Section, GFZ German Research Centre for Geosciences, Telegrafenberg, Potsdam, GermanyHydrology Section, GFZ German Research Centre for Geosciences, Telegrafenberg, Potsdam, GermanyInstitute for Environmental Sciences and Geography, University of Potsdam, Potsdam, Germany<p>Tracer data have been successfully used for hydrograph separation in glacierized basins. However, in these basins uncertainties of the hydrograph separation are large and are caused by the spatiotemporal variability in the tracer signatures of water sources, the uncertainty of water sampling, and the mixing model uncertainty. In this study, we used electrical conductivity (EC) measurements and two isotope signatures (<span class="inline-formula"><i>δ</i></span><span class="inline-formula"><sup>18</sup>O</span> and <span class="inline-formula"><i>δ</i></span><span class="inline-formula"><sup>2</sup>H</span>) to label the runoff components, including groundwater, snow and glacier meltwater, and rainfall, in a Central Asian glacierized basin. The contributions of runoff components (CRCs) to the total runoff and the corresponding uncertainty were quantified by two mixing approaches, namely a traditional end-member mixing approach (abbreviated as EMMA) and a Bayesian end-member mixing approach. The performance of the two mixing approaches was compared in three seasons that are distinguished as the cold season, snowmelt season, and glacier melt season. The results show the following points. (1) The Bayesian approach generally estimated smaller uncertainty ranges for the CRC when compared to the EMMA. (2) The Bayesian approach tended to be less sensitive to the sampling uncertainties of meltwater than the EMMA. (3) Ignoring the model uncertainty caused by the isotope fractionation likely led to an overestimated rainfall contribution and an underestimated meltwater share in the melt seasons. Our study provides the first comparison of the two end-member mixing approaches for hydrograph separation in glacierized basins and gives insight into the application of tracer-based mixing approaches in similar basins.</p>https://www.hydrol-earth-syst-sci.net/24/3289/2020/hess-24-3289-2020.pdf
collection DOAJ
language English
format Article
sources DOAJ
author Z. He
Z. He
K. Unger-Shayesteh
S. Vorogushyn
S. M. Weise
D. Duethmann
D. Duethmann
O. Kalashnikova
A. Gafurov
B. Merz
B. Merz
spellingShingle Z. He
Z. He
K. Unger-Shayesteh
S. Vorogushyn
S. M. Weise
D. Duethmann
D. Duethmann
O. Kalashnikova
A. Gafurov
B. Merz
B. Merz
Comparing Bayesian and traditional end-member mixing approaches for hydrograph separation in a glacierized basin
Hydrology and Earth System Sciences
author_facet Z. He
Z. He
K. Unger-Shayesteh
S. Vorogushyn
S. M. Weise
D. Duethmann
D. Duethmann
O. Kalashnikova
A. Gafurov
B. Merz
B. Merz
author_sort Z. He
title Comparing Bayesian and traditional end-member mixing approaches for hydrograph separation in a glacierized basin
title_short Comparing Bayesian and traditional end-member mixing approaches for hydrograph separation in a glacierized basin
title_full Comparing Bayesian and traditional end-member mixing approaches for hydrograph separation in a glacierized basin
title_fullStr Comparing Bayesian and traditional end-member mixing approaches for hydrograph separation in a glacierized basin
title_full_unstemmed Comparing Bayesian and traditional end-member mixing approaches for hydrograph separation in a glacierized basin
title_sort comparing bayesian and traditional end-member mixing approaches for hydrograph separation in a glacierized basin
publisher Copernicus Publications
series Hydrology and Earth System Sciences
issn 1027-5606
1607-7938
publishDate 2020-06-01
description <p>Tracer data have been successfully used for hydrograph separation in glacierized basins. However, in these basins uncertainties of the hydrograph separation are large and are caused by the spatiotemporal variability in the tracer signatures of water sources, the uncertainty of water sampling, and the mixing model uncertainty. In this study, we used electrical conductivity (EC) measurements and two isotope signatures (<span class="inline-formula"><i>δ</i></span><span class="inline-formula"><sup>18</sup>O</span> and <span class="inline-formula"><i>δ</i></span><span class="inline-formula"><sup>2</sup>H</span>) to label the runoff components, including groundwater, snow and glacier meltwater, and rainfall, in a Central Asian glacierized basin. The contributions of runoff components (CRCs) to the total runoff and the corresponding uncertainty were quantified by two mixing approaches, namely a traditional end-member mixing approach (abbreviated as EMMA) and a Bayesian end-member mixing approach. The performance of the two mixing approaches was compared in three seasons that are distinguished as the cold season, snowmelt season, and glacier melt season. The results show the following points. (1) The Bayesian approach generally estimated smaller uncertainty ranges for the CRC when compared to the EMMA. (2) The Bayesian approach tended to be less sensitive to the sampling uncertainties of meltwater than the EMMA. (3) Ignoring the model uncertainty caused by the isotope fractionation likely led to an overestimated rainfall contribution and an underestimated meltwater share in the melt seasons. Our study provides the first comparison of the two end-member mixing approaches for hydrograph separation in glacierized basins and gives insight into the application of tracer-based mixing approaches in similar basins.</p>
url https://www.hydrol-earth-syst-sci.net/24/3289/2020/hess-24-3289-2020.pdf
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