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

Xu Fei, Esther; Harman, Ciaran Joseph

doi:https://doi.org/10.5194/hess-26-1977-2022

Articles | Volume 26, issue 8

https://doi.org/10.5194/hess-26-1977-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/hess-26-1977-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 26, issue 8

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

Data sets

Example CHEMMA application code for the technical note E. Xu Fei https://doi.org/10.5281/zenodo.4116082

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.