Articles | Volume 23, issue 12
https://doi.org/10.5194/hess-23-5059-2019
https://doi.org/10.5194/hess-23-5059-2019
Technical note
 | 
16 Dec 2019
Technical note |  | 16 Dec 2019

Technical note: Uncertainty in multi-source partitioning using large tracer data sets

Alicia Correa, Diego Ochoa-Tocachi, and Christian Birkel

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Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
ED: Reconsider after major revisions (further review by editor and referees) (17 Sep 2019) by Markus Hrachowitz
AR by Alicia Correa on behalf of the Authors (18 Sep 2019)  Author's response   Manuscript 
ED: Referee Nomination & Report Request started (18 Sep 2019) by Markus Hrachowitz
RR by Anonymous Referee #2 (27 Sep 2019)
RR by Anonymous Referee #1 (11 Oct 2019)
ED: Publish subject to minor revisions (review by editor) (21 Oct 2019) by Markus Hrachowitz
AR by Alicia Correa on behalf of the Authors (25 Oct 2019)
ED: Publish as is (30 Oct 2019) by Markus Hrachowitz
AR by Alicia Correa on behalf of the Authors (07 Nov 2019)
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Short summary
The applications and availability of large tracer data sets have vastly increased in recent years leading to research into the contributions of multiple sources to a mixture. We introduce a method based on Taylor series approximation to estimate the uncertainties of such sources' contributions. The method is illustrated with examples of hydrology (14 tracers) and a MATLAB code is provided for reproducibility. This method can be generalized to any number of tracers across a range of disciplines.