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| Titel |
Uncertainties in selected river water quality data |
| VerfasserIn |
M. Rode, U. Suhr |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1027-5606
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| Digitales Dokument |
URL |
| Erschienen |
In: Hydrology and Earth System Sciences ; 11, no. 2 ; Nr. 11, no. 2 (2007-02-13), S.863-874 |
| Datensatznummer |
250009220
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| Publikation (Nr.) |
 copernicus.org/hess-11-863-2007.pdf |
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| Zusammenfassung |
| Monitoring of surface waters is primarily done to detect the status and
trends in water quality and to identify whether observed trends arise from
natural or anthropogenic causes. Empirical quality of river water quality
data is rarely certain and knowledge of their uncertainties is essential to
assess the reliability of water quality models and their predictions. The
objective of this paper is to assess the uncertainties in selected river
water quality data, i.e. suspended sediment, nitrogen fraction, phosphorus
fraction, heavy metals and biological compounds. The methodology used to
structure the uncertainty is based on the empirical quality of data and the
sources of uncertainty in data (van Loon et al., 2005). A literature review
was carried out including additional experimental data of the Elbe river. All
data of compounds associated with suspended particulate matter have
considerable higher sampling uncertainties than soluble concentrations. This
is due to high variability within the cross section of a given river. This
variability is positively correlated with total suspended particulate matter
concentrations. Sampling location has also considerable effect on the
representativeness of a water sample. These sampling uncertainties are highly
site specific. The estimation of uncertainty in sampling can only be achieved
by taking at least a proportion of samples in duplicates. Compared to
sampling uncertainties, measurement and analytical uncertainties are much
lower. Instrument quality can be stated well suited for field and laboratory
situations for all considered constituents. Analytical errors can contribute
considerably to the overall uncertainty of river water quality data.
Temporal autocorrelation of river water quality data is present but
literature on general behaviour of water quality compounds is rare. For meso
scale river catchments (500–3000 km2) reasonable yearly dissolved load
calculations can be achieved using biweekly sample frequencies. For suspended
sediments none of the methods investigated produced very reliable load
estimates when weekly concentrations data were used. Uncertainties associated
with loads estimates based on infrequent samples will decrease with
increasing size of rivers. |
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