Long-term behaviour and cross-correlation water quality analysis of the River Elbe, Germany.
This study analyses weekly data samples from the river Elbe at Magdeburg between 1984 and 1996 to investigate the changes in metabolism and water quality in the river Elbe since the German reunification in 1990. Modelling water quality variables by autoregressive component models and ARIMA models reveals the improvement of water quality due to the reduction of waste water emissions since 1990. The models are used to determine the long-term and seasonal behaviour of important water quality variables. Organic and heavy metal pollution parameters showed a significant decrease since 1990, however, no significant change of chlorophyll-a as a measure for primary production could be found. A new procedure for testing the significance of a sample correlation coefficient is discussed, which is able to detect spurious sample correlation coefficients without making use of time-consuming prewhitening. The cross-correlation analysis is applied to hydrophysical, biological, and chemical water quality variables of the river Elbe since 1984. Special emphasis is laid on the detection of spurious sample correlation coefficients.
Lehmann
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A
Department of Mathematics, Otto-von-Guericke-University Magdeburg, Institute of Mathematical Stochastics, Germany.
Rode
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M
D005618:Fresh Water / Q000032:analysis*; D005858:Germany; D008962:Models, Theoretical; D011786:Quality Control; D012621:Seasons; D013997:Time Factors; D014876:Water Pollution / Q000032:analysis* / Q000517:prevention & control