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Water Resources Research

Uncertainty estimation of end-member mixing using generalized likelihood uncertainty estimation (GLUE), applied in a lowland catchment

Authors

  • Joost R. Delsman,

    Corresponding author
    1. Department of Soil and Groundwater, Deltares, Utrecht, Netherlands
    2. Critical Zone Hydrology Group, Department of Earth Sciences, VU University Amsterdam, Amsterdam, Netherlands
    • Corresponding author: J. R. Delsman, Department of Soil and Groundwater, Deltares, Utrecht, Netherlands, PO Box 85467, NL-3508 AL, Utrecht, Netherlands. (joost.delsman@deltares.nl)

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  • Gualbert H. P. Oude Essink,

    1. Department of Soil and Groundwater, Deltares, Utrecht, Netherlands
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  • Keith J. Beven,

    1. Lancaster Environment Center, Lancaster University, Lancaster, UK
    2. Geocentrum, Uppsala University, Uppsala, Sweden
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  • Pieter J. Stuyfzand

    1. Critical Zone Hydrology Group, Department of Earth Sciences, VU University Amsterdam, Amsterdam, Netherlands
    2. KWR Watercycle Research Institute, Nieuwegein, Netherlands
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Abstract

[1] End-member mixing models have been widely used to separate the different components of a hydrograph, but their effectiveness suffers from uncertainty in both the identification of end-members and spatiotemporal variation in end-member concentrations. In this paper, we outline a procedure, based on the generalized likelihood uncertainty estimation (GLUE) framework, to more inclusively evaluate uncertainty in mixing models than existing approaches. We apply this procedure, referred to as G-EMMA, to a yearlong chemical data set from the heavily impacted agricultural Lissertocht catchment, Netherlands, and compare its results to the “traditional” end-member mixing analysis (EMMA). While the traditional approach appears unable to adequately deal with the large spatial variation in one of the end-members, the G-EMMA procedure successfully identified, with varying uncertainty, contributions of five different end-members to the stream. Our results suggest that the concentration distribution of “effective” end-members, that is, the flux-weighted input of an end-member to the stream, can differ markedly from that inferred from sampling of water stored in the catchment. Results also show that the uncertainty arising from identifying the correct end-members may alter calculated end-member contributions by up to 30%, stressing the importance of including the identification of end-members in the uncertainty assessment.

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