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| Titel |
Comparing geological and statistical approaches for element selection in sediment tracing research |
| VerfasserIn |
J. Patrick Laceby, Joe McMahon, Olivier Evrard, Jon Olley |
| Konferenz |
EGU General Assembly 2015
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 17 (2015) |
| Datensatznummer |
250106955
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| Publikation (Nr.) |
 EGU/EGU2015-6640.pdf |
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| Zusammenfassung |
| Elevated suspended sediment loads reduce reservoir capacity and significantly increase the
cost of operating water treatment infrastructure, making the management of sediment supply
to reservoirs of increasingly importance. Sediment fingerprinting techniques can be used to
determine the relative contributions of different sources of sediment accumulating in
reservoirs. The objective of this research is to compare geological and statistical
approaches to element selection for sediment fingerprinting modelling. Time-integrated
samplers (n=45) were used to obtain source samples from four major subcatchments
flowing into the Baroon Pocket Dam in South East Queensland, Australia. The
geochemistry of potential sources were compared to the geochemistry of sediment cores
(n=12) sampled in the reservoir. The geochemical approach selected elements for
modelling that provided expected, observed and statistical discrimination between
sediment sources. Two statistical approaches selected elements for modelling with the
Kruskal-Wallis H-test and Discriminatory Function Analysis (DFA). In particular, two
different significance levels (0.05 & 0.35) for the DFA were included to investigate the
importance of element selection on modelling results. A distribution model determined
the relative contributions of different sources to sediment sampled in the Baroon
Pocket Dam. Elemental discrimination was expected between one subcatchment (Obi
Obi Creek) and the remaining subcatchments (Lexys, Falls and Bridge Creek). Six
major elements were expected to provide discrimination. Of these six, only Fe2O3
and SiO2 provided expected, observed and statistical discrimination. Modelling
results with this geological approach indicated 36% (+/- 9%) of sediment sampled in
the reservoir cores were from mafic-derived sources and 64% (+/- 9%) were from
felsic-derived sources. The geological and the first statistical approach (DFA0.05)
differed by only 1% (Ïă 5%) for 5 out of 6 model groupings with only the Lexys Creek
modelling results differing significantly (35%). The statistical model with expanded
elemental selection (DFA0.35) differed from the geological model by an average of 30%
for all 6 models. Elemental selection for sediment fingerprinting therefore has the
potential to impact modeling results. Accordingly is important to incorporate both
robust geological and statistical approaches when selecting elements for sediment
fingerprinting. For the Baroon Pocket Dam, management should focus on reducing
the supply of sediments derived from felsic sources in each of the subcatchments. |
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