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| Titel |
A fingerprinting mixing model approach to generate uniformly representative solutions for distributed contributions of sediment sources in a Pyrenean drainage basin |
| VerfasserIn |
Leticia Palazón, Leticia Gaspar, Borja Latorre, Will Blake, Ana Navas |
| Konferenz |
EGU General Assembly 2014
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 16 (2014) |
| Datensatznummer |
250097216
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| Publikation (Nr.) |
 EGU/EGU2014-12771.pdf |
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| Zusammenfassung |
| Spanish Pyrenean reservoirs are under pressure from high sediment yields in contributing
catchments. Sediment fingerprinting approaches offer potential to quantify the contribution of
different sediment sources, evaluate catchment erosion dynamics and develop management
plans to tackle the reservoir siltation problems. The drainage basin of the Barasona reservoir
(1509 km2), located in the Central Spanish Pyrenees, is an alpine-prealpine agroforest basin
supplying sediments to the reservoir at an annual rate of around 350 t km-2 with implications
for reservoir longevity. The climate is mountain type, wet and cold, with both Atlantic and
Mediterranean influences. Steep slopes and the presence of deep and narrow gorges favour
rapid runoff and large floods. The ability of geochemical fingerprint properties to
discriminate between the sediment sources was investigated by conducting the nonparametric
Kruskal-Wallis H-test and a stepwise discriminant function analysis (minimization of
Wilk’s lambda). This standard procedure selects potential fingerprinting properties as
optimum composite fingerprint to characterize and discriminate between sediment
sources to the reservoir. Then the contribution of each potential sediment source was
assessed by applying a Monte Carlo mixing model to obtain source proportions for the
Barasona reservoir sediment samples. The Monte Carlo mixing model was written in C
programming language and designed to deliver a user-defined number possible solutions. A
Combinatorial Principals method was used to identify the most probable solution
with associated uncertainty based on source variability. The unique solution for
each sample was characterized by the mean value and the standard deviation of the
generated solutions and the lower goodness of fit value applied. This method is
argued to guarantee a similar set of representative solutions in all unmixing cases
based on likelihood of occurrence. Soil samples for the different potential sediment
sources of the drainage basin were compared with samples from the reservoir using a
range of different fingerprinting properties (i.e. mass activities of environmental
radionuclides, elemental composition and magnetic susceptibility) analyzed in the
< 63 μm sediment fraction. In this case, the 100 best results from 106 generated
iterations were selected obtaining a goodness of fit higher than 0.76. The preliminary
results using this new data processing methodology for samples collected in the
reservoir allowed us to identify cultivated fields and badlands as main potential
sources of sediments to the reservoir. These findings support the appropriate use of
the fingerprinting methodology in a Spanish Pyrenees basin, which will enable
us to better understand the basin sediment production of the Barasona reservoir. |
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