DOI: 10.1371/journal.pone.0348737 ISSN: 1932-6203

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

Falko Wagner, Ianina Kopecki, Jelger Elings, Ulf Enders, Andreas Lindig, Kathrin Maltzahn, Tom Roessger, Márcio S. Roth, Mansour Royan, Jürgen Stamm, Stefan Hoerner
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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

m s m
. 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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