File:Rode 2007 - Uncertainties in selected river water quality data.pdf
Rode_2007_-_Uncertainties_in_selected_river_water_quality_data.pdf (file size: 358 KB, MIME type: application/pdf)
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 as- sess the reliability of water quality models and their predic- tions. 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 bi- ological 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 liter- ature review was carried out including additional experimen- tal 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 sus- pended 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 du- plicates. Compared to sampling uncertainties, measurement and analytical uncertainties are much lower. Instrument qual- ity can be stated well suited for field and laboratory situations for all considered constituents. Analytical errors can con- tribute considerably to the overall uncertainty of river water quality data.
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|current||13:02, January 31, 2015||(358 KB)||DataRonin||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 know...|