Automatic water mixing event identification in the Koljö fjord observatory data

  • Markus GötzEmail author
  • Mikhail Kononets
  • Christian Bodenstein
  • Morris Riedel
  • Matthias Book
  • Olafur Petur Palsson


This study addresses the task of automatically identifying water mixing events in the multivariate time series of salinity, temperature and dissolved oxygen provided by the Koljö fjord observatory. The observatory is used to test new underwater sensory technology and to monitor water quality with respect to hypoxia and oxygenation in the fjord and has been collecting data since April 2011. The fjord water properties change, manifesting as peaks or drops of dissolved oxygen, salinity and temperature, when affected by inflows of new water originating from the open sea or by rivers connected to the fjord system. An acute state of oxygen depletion can harm wildlife and the ecosystem permanently. The major challenge for the analysis is that the water property changes are marked by highly varying peak strength and correlation between the signals. The proposed data-driven analysis method extends existing univariate outlier detection approaches, based on clustering techniques, to identify the water mixing events. It incorporates three major steps: 1. smoothing of the input data, to counter noise, 2. individual outlier detection within the separate variables, 3. clustering of the results using the DBSCAN clustering algorithm to determine the anomalous events. The proposed approach is able to detect the water mixing events with a \(F{\textit{1}}\)-measure of 0.885, a precision of 0.931—that is 93.1% of all events have been correctly detected—and a recall of 0.843–84.3% of events that should have been found actually also have been. Using the proposed method, the oceanographers can be informed automatically about the status of the fjord without manual interaction or physical presence at the experiment site.


Multivariate time series analysis Koljö fjord observatory Water mixing event detection Clustering DBSCAN 



The installation of the Koljö fjord cabled observatory was carried out by the University of Gothenburg in collaboration with MARUM, University of Bremen, Germany, and funded by the European Commission projects ESONET-NoE (contract number 036851), HYPOX (Grant agreement number 226213) and EMSO (Grant agreement number 211816). This work is also supported by Aanderaa Data Instruments AS providing the Doppler Current Profiler instruments, other material and financial support to run the Koljö fjord observatory.

Compliance with ethical standards

Conflict of interest

On behalf of all authors, the corresponding author states that there is no conflict of interest.


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Juelich Supercomputing CenterResearch Center JuelichJülichGermany
  2. 2.Department of Marine ScienceUniversity of GothenburgGöteborgSweden
  3. 3.Mechanical Engineering and Computer Science, Faculty for Industrial EngineeringUniversity of IcelandReykjavíkIceland

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