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Comparison of Methods for Normalisation and Trend Testing of Water Quality Data
Linköping University, Faculty of Arts and Sciences. Linköping University, Department of Mathematics, Statistics .
2004 (English)In: The joint meeting of TIES 2004 and Accuracy 2004,2004, 2004Conference paper (Other academic)
Abstract [en]

To correctlyassesstrends in water quality data, influencing variables suchasdischarge or temperature must betaken into account. This canbedone by using i one-step procedures like the PartialMann-KendallPMK test ormultiple regression, or ii two-steptechniques thatinclude a normalisation followed by a trend test ontheresiduals.Which approach is most appropriate depends strongly ontherelationship between the response variableunder considerationandthe influencing variables. For example, PMK tests can besuperiorif there are long andvarying time lags in the waterqualityresponse. Two-step procedures are particularly useful whentheshape of thetemporal trend is the primary interest, but they canbemisleading if one of the influencing variables itselfexhibitsatrend or long-term tendency. The present study discussestheadvantages and disadvantages of some trendtesting techniques,usingSwedish water quality data to illustrate the properties ofthemethods.

Place, publisher, year, edition, pages
Keyword [en]
long-term changes in covariate, non-monotonic changes, long memory effects, seasonal variation
National Category
URN: urn:nbn:se:liu:diva-22685Local ID: 1977OAI: diva2:242998
Available from: 2009-10-07 Created: 2009-10-07

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