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Peer-reviewedCC BY 4.0PLOS One

Behavior of downstream swimming brown trout in accelerating and high flow velocity - Movement matters

  • Falko Wagner1
  • Ianina Kopecki2
  • Jelger Elings3
  • Ulf Enders4
  • Andreas Lindig5
  • Kathrin Maltzahn6
  • Tom Roessger
  • Márcio S. Roth
  • Mansour Royan
  • Jürgen Stamm
  • Stefan Hoerner
6 affiliations
  1. 1Institute of Freshwater Ecology and Fish Biology (IGF) Jena, Jena, Germany
  2. 2SJE – Ecohydraulic Engineering GmbH, Stuttgart, Germany
  3. 3Department of Fish Ecology and Evolution, Eawag: Swiss Federal Institute of Aquatic Science and Technology, Kastanienbaum, Switzerland
  4. 4Institute of Hydraulic Engineering and Technical Hydromechanics (IWD), TUD Dresden University of Technology, Dresden, Germany
  5. 5Laboratory of Geophysical and Industrial Flows (LEGI), Grenoble INP, CNRS, University Grenoble-Alpes, Saint-Martin-d'Hères, France
  6. 6Institute of Fluid Dynamics and Thermodynamics (ISUT), Otto von Guericke University Magdeburg, Magdeburg, Germany
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Abstract

Studies on active and sedated fish passing through turbines and pumps show different mortality and injury rates for both cases. Consequently, fish behavior appears to play a substantial role in these outcomes. However, direct behavioral observations in hydraulic machines using quantitative parameters to draw conclusions about the underlying mechanisms are hardly possible and remain understudied. In this study, we examined the behavior of adult brown trout (Salmo trutta) in an experimental flume under hydraulic conditions characterized by strong flow acceleration and high velocities, two key hydraulic features of turbine and pump intakes. Fish movement behavior was analyzed based on a quantitative approach to enable the analysis of swimming behavior even in flow velocities exceeding the sprint swimming speed of fish. The application of Hidden Markov Models (HMM) to analyze activity states and movement modes of fish from video tracking data demonstrated significant effects of the spatial velocity gradient (SVG) and flow velocity on fish behavior. Notably, SVG emerged as the primary trigger for avoidance reactions when exceeding a threshold of 0.31 msm. Fish exhibited distinct movement patterns under dark and daylight conditions, with more avoidance reactions in darkness. Whereas a considerable proportion of fish in daylight increased their swimming activity in the zone where flow velocity exceeded sprint swimming speed, in dark conditions no activity peak occurred in the same zone. The results illustrate how hydraulic conditions and light influence fish behavior. Integrating the behavioral rules identified in this study into numerical mortality‑risk models could substantially improve their predictive accuracy. This enhanced understanding can support the design and optimization of fish protection solutions at hydropower facilities and pumping stations.

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Cite

BibTeXRIS
BibTeX
@article{wagner2026behavior,
  title = {{Behavior of downstream swimming brown trout in accelerating and high flow velocity - Movement matters}},
  author = {Falko Wagner and Ianina Kopecki and Jelger Elings and Ulf Enders and Andreas Lindig and Kathrin Maltzahn and Tom Roessger and Márcio S. Roth and Mansour Royan and Jürgen Stamm and Stefan Hoerner},
  journal = {PLOS One},
  year = {2026},
  month = sep,
  doi = {10.1371/journal.pone.0348737},
  url = {https://doi.org/10.1371/journal.pone.0348737},
  note = {CC BY 4.0},
}
RIS
TY  - JOUR
TI  - Behavior of downstream swimming brown trout in accelerating and high flow velocity - Movement matters
AU  - Falko Wagner
AU  - Ianina Kopecki
AU  - Jelger Elings
AU  - Ulf Enders
AU  - Andreas Lindig
AU  - Kathrin Maltzahn
AU  - Tom Roessger
AU  - Márcio S. Roth
AU  - Mansour Royan
AU  - Jürgen Stamm
AU  - Stefan Hoerner
PY  - 2026
DA  - 2026/09/30
JO  - PLOS One
DO  - 10.1371/journal.pone.0348737
UR  - https://doi.org/10.1371/journal.pone.0348737
AB  - Studies on active and sedated fish passing through turbines and pumps show different mortality and injury rates for both cases. Consequently, fish behavior appears to play a substantial role in these outcomes. However, direct behavioral observations in hydraulic machines using quantitative parameters to draw conclusions about the underlying mechanisms are hardly possible and remain understudied. In this study, we examined the behavior of adult brown trout (Salmo trutta) in an experimental flume under hydraulic conditions characterized by strong flow acceleration and high velocities, two key hydraulic features of turbine and pump intakes. Fish movement behavior was analyzed based on a quantitative approach to enable the analysis of swimming behavior even in flow velocities exceeding the sprint swimming speed of fish. The application of Hidden Markov Models (HMM) to analyze activity states and movement modes of fish from video tracking data demonstrated significant effects of the spatial velocity gradient (SVG) and flow velocity on fish behavior. Notably, SVG emerged as the primary trigger for avoidance reactions when exceeding a threshold of 0.31 msm. Fish exhibited distinct movement patterns under dark and daylight conditions, with more avoidance reactions in darkness. Whereas a considerable proportion of fish in daylight increased their swimming activity in the zone where flow velocity exceeded sprint swimming speed, in dark conditions no activity peak occurred in the same zone. The results illustrate how hydraulic conditions and light influence fish behavior. Integrating the behavioral rules identified in this study into numerical mortality‑risk models could substantially improve their predictive accuracy. This enhanced understanding can support the design and optimization of fish protection solutions at hydropower facilities and pumping stations.
SN  - 1932-6203
ER  -