Articles | Volume 26, issue 8
https://doi.org/10.5194/hess-26-1977-2022
https://doi.org/10.5194/hess-26-1977-2022
Research article
 | 
22 Apr 2022
Research article |  | 22 Apr 2022

A data-driven method for estimating the composition of end-members from stream water chemistry time series

Esther Xu Fei and Ciaran Joseph Harman

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Cited articles

Ali, G. A., Roy, A. G., Turmel, M. C., and Courchesne, F.: Source-to-stream connectivity assessment through end-member mixing analysis, J. Hydrol., 392, 119–135, https://doi.org/10.1016/j.jhydrol.2010.07.049, 2010. a
Ashley, R. and Lloyd, J.: An example of the use of factor analysis and cluster analysis in groundwater chemistry interpretation, J. Hydrol., 39, 355–364, 1978. a
Babaki, B.: COP-Kmeans version 1.5, Zenodo, https://doi.org/10.5281/zenodo.831850, 2017. a
Barbeta, A. and Peñuelas, J.: Relative contribution of groundwater to plant transpiration estimated with stable isotopes, Scient. Rep., 7, 1–10, https://doi.org/10.1038/s41598-017-09643-x, 2017. a
Barthold, F. K., Tyralla, C., Schneider, K., Vaché, K. B., Frede, H.-G., and Breuer, L.: How many tracers do we need for end member mixing analysis (EMMA)? A sensitivity analysis, Water Resour. Res., 47, 1–14, https://doi.org/10.1029/2011WR010604, 2011. a
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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 do not 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.