Technical note: Uncertainty in multi-source partitioning using large tracer data sets
<p>The availability of large tracer data sets opened up the opportunity to investigate multiple source contributions to a mixture. However, the source contributions may be uncertain and, apart from Bayesian approaches, to date there are only solid methods to estimate such uncertainties for two...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2019-12-01
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| Series: | Hydrology and Earth System Sciences |
| Online Access: | https://www.hydrol-earth-syst-sci.net/23/5059/2019/hess-23-5059-2019.pdf |
| Summary: | <p>The availability of large tracer data sets opened up the opportunity to
investigate multiple source contributions to a mixture. However, the source
contributions may be uncertain and, apart from Bayesian approaches, to date
there are only solid methods to estimate such uncertainties for two and
three sources. We introduce an alternative uncertainty estimation method for
four sources based on multiple tracers as input data. Taylor series
approximation is used to solve the set of linear mass balance equations. We
illustrate the method to compute individual uncertainties in the calculation
of source contributions to a mixture, with an example from hydrology, using
a 14-tracer set from water sources and streamflow from a tropical,
high-elevation catchment. Moreover, this method has the potential to be
generalized to any number of tracers across a range of disciplines.</p> |
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| ISSN: | 1027-5606 1607-7938 |