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Preprints
https://doi.org/10.5194/hess-2020-250
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-2020-250
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: technical note 15 Jun 2020

Submitted as: technical note | 15 Jun 2020

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This preprint is currently under review for the journal HESS.

Technical Note: A data-driven method for estimating the composition of end-members from streamwater chemistry observations

Esther Xu Fei1 and Ciaran Joseph Harman1,2 Esther Xu Fei and Ciaran Joseph Harman
  • 1Department of Environmental Health and Engineering, Johns Hopkins University
  • 2Department of Earth and Planetary Science, Johns Hopkins University

Abstract. End-Member Mixing Analysis (EMMA) is a method of interpreting streamwater chemistry variations, and is widely used for chemical hydrograph separation. It is based on the assumption that the streamwater is a mixture of varying contributions from relatively time-invariant source solutions (end-members). These end-members are typically identified by collecting additional measurements of candidate end-members from within the watershed, and comparing these to the observations. This technical note introduces a complementary, data-driven method: Convex-Hull End-Member Mixing Analysis (CHEMMA), to infer the end-member compositions and their associated uncertainties from the streamwater observations alone. The method involves two steps. The first step uses Convex-Hull Non-negative Matrix Factorization (CH-NMF) to infer possible end-member compositions by searching for a simplex that optimally encloses the streamwater observations. The second step uses Constrained K-means Clustering (COP-KMEANS) to classify the results from repeated applications of CH-NMF to analyze the uncertainty associated with the algorithm. In an example application using the 1986 to 1988 Panola Mountain Research Watershed dataset, CHEMMA is able to robustly reproduce the three field-measured end-members found in previous research using only the streawater chemical observations. It also suggests the existence of a fourth end-member. Further work is needed to explore the constraints and capabilities of this approach.

Esther Xu Fei and Ciaran Joseph Harman

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Status: open (until 10 Aug 2020)
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Esther Xu Fei and Ciaran Joseph Harman

Model code and software

CHEMMA example application for Panola Mountain Research Dataset E. X. Fei and C. J. Harman https://doi.org/10.5281/zenodo.3841218

Esther Xu Fei and Ciaran Joseph Harman

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Latest update: 13 Jul 2020
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Short summary
Water in streams is a mixture of water from many sources. It is sometimes possible to identify the chemical fingerprint of each source, and track the time-varying contribution of that source to the total flow rate. But what if you don't know the chemical fingerprint of each source? Can you simultaneously identify the sources (called 'end-members'), and separate the water into contributions from each, using only samples of water from the stream? Here we suggest a method for doing just that.
Water in streams is a mixture of water from many sources. It is sometimes possible to identify...
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