Articles | Volume 22, issue 8
https://doi.org/10.5194/hess-22-4401-2018
https://doi.org/10.5194/hess-22-4401-2018
Research article
 | 
21 Aug 2018
Research article |  | 21 Aug 2018

Detecting dominant changes in irregularly sampled multivariate water quality data sets

Christian Lehr, Ralf Dannowski, Thomas Kalettka, Christoph Merz, Boris Schröder, Jörg Steidl, and Gunnar Lischeid

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Latest update: 27 Mar 2024
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Short summary
We suggested and tested an exploratory approach for the detection of dominant changes in multivariate water quality data sets with irregular sampling in space and time. The approach is especially recommended for the exploratory assessment of existing long-term low-frequency multivariate water quality monitoring data.