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Mortality assessment for adult European eels (Anguilla Anguilla) during turbine passage using CFD modelling

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  • Klopries, Elena-Maria
  • Schüttrumpf, Holger

Abstract

Collisions, shear events and barotrauma are severe causes of fish mortality in a hydroelectric turbine. Fish-adapted turbine management and environmentally enhanced turbines can be mitigation measures. To use those measures efficiently, knowledge about turbine mortality is needed. In this study, a combination of CFD modelling, fish passage modelling and mortality assessment was used to evaluate mortality for different operating points of a Kaplan bulb turbine for adult European eels (anguilla anguilla). Calculated mortality due to collisions varied from 22% to 37%, due to shear events from 7% to 14% and due to barotrauma from 0% to 18%. The operating points with discharges between 70% and 85% of maximum discharge yielded the lowest mortality values. This supports the idea that a fish-adapted turbine management is possible that gives preference to operating points that are less hazardous to fish than others. Based on this approach it is possible to distinguish the locations within a turbine where hazardous hydraulic conditions occur making it a valuable tool in the design process and the biological performance evaluation of a turbine-management plan without needing to implement it first. Furthermore, no animal experiments are necessary for this approach.

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  • Klopries, Elena-Maria & Schüttrumpf, Holger, 2020. "Mortality assessment for adult European eels (Anguilla Anguilla) during turbine passage using CFD modelling," Renewable Energy, Elsevier, vol. 147(P1), pages 1481-1490.
    • Handle: RePEc:eee:renene:v:147:y:2020:i:p1:p:1481-1490
    DOI: 10.1016/j.renene.2019.09.112
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    References listed on IDEAS

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    1. Fu, Tao & Deng, Zhiqun Daniel & Duncan, Joanne P. & Zhou, Daqing & Carlson, Thomas J. & Johnson, Gary E. & Hou, Hongfei, 2016. "Assessing hydraulic conditions through Francis turbines using an autonomous sensor device," Renewable Energy, Elsevier, vol. 99(C), pages 1244-1252.
    2. Deng, Zhiqun & Carlson, Thomas J. & Ploskey, Gene R. & Richmond, Marshall C. & Dauble, Dennis D., 2007. "Evaluation of blade-strike models for estimating the biological performance of Kaplan turbines," Ecological Modelling, Elsevier, vol. 208(2), pages 165-176.
    3. Zangiabadi, E. & Masters, I. & Williams, Alison J. & Croft, T.N. & Malki, R. & Edmunds, M. & Mason-Jones, A. & Horsfall, I., 2017. "Computational prediction of pressure change in the vicinity of tidal stream turbines and the consequences for fish survival rate," Renewable Energy, Elsevier, vol. 101(C), pages 1141-1156.
    4. Hongfei Hou & Zhiqun Daniel Deng & Jayson J. Martinez & Tao Fu & Joanne P. Duncan & Gary E. Johnson & Jun Lu & John R. Skalski & Richard L. Townsend & Li Tan, 2018. "A Hydropower Biological Evaluation Toolset (HBET) for Characterizing Hydraulic Conditions and Impacts of Hydro-Structures on Fish," Energies, MDPI, vol. 11(4), pages 1-13, April.
    5. Romero-Gomez, Pedro & Richmond, Marshall C., 2014. "Simulating blade-strike on fish passing through marine hydrokinetic turbines," Renewable Energy, Elsevier, vol. 71(C), pages 401-413.
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    1. Linda Vikström & Kjell Leonardsson & Johan Leander & Samuel Shry & Olle Calles & Gustav Hellström, 2020. "Validation of Francis–Kaplan Turbine Blade Strike Models for Adult and Juvenile Atlantic Salmon (Salmo Salar, L.) and Anadromous Brown Trout (Salmo Trutta, L.) Passing High Head Turbines," Sustainability, MDPI, vol. 12(16), pages 1-13, August.
    2. Singh, Rajesh K. & Romero-Gomez, Pedro & Colotelo, Alison H. & Perkins, William A. & Richmond, Marshall C., 2022. "Computational studies of hydraulic stressors for biological performance assessment in a hydropower plant with Kaplan turbine," Renewable Energy, Elsevier, vol. 199(C), pages 768-781.
    3. Powalla, Dennis & Hoerner, Stefan & Cleynen, Olivier & Thévenin, Dominique, 2022. "A numerical approach for active fish behaviour modelling with a view toward hydropower plant assessment," Renewable Energy, Elsevier, vol. 188(C), pages 957-966.

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