Long-term behaviour and cross-correlation analysis of water quality parameters of the Elbe river at Magdeburg, Germany

by Lehmann, A.; Rode, M.


Preprint series: 00-08, Preprints

62M10 Time series, auto-correlation, regression, etc., See Also { 90A20}
62G07 Curve estimation (nonparametric regression, density estimation, etc.)
86A05 Hydrology, hydrography, oceanography, See also {76B15, 76B20, 76B25, 76C15, 76E20, 76Q05, 76Rxx, 76U05}


Abstract: This study analyses weekly data samples from the Elbe river at Magdeburg between 1984 and 1996 to investigate the changes in metabolism and water quality in the Elbe river since the German reunification in 1990. Modeling water quality variables by univariate time series models such as 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 parameters. A new procedure for testing the significance of a sample correlation coefficient is discussed. The cross-correlation analysis is applied to hydrophysical, biological, and chemical water quality variables of the Elbe river since 1990. Special emphasis is laid on the detection of spurious sample correlation coefficients.

Keywords: Water quality, cross-correlation analysis, timeseries analysis, ARIMA model

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