Amado, A.

English

ScholarWorks@UMass Amherst

An approach to model swimming behavior of smolts in the forebay of hydro dams

University of Massachusetts AmherstScholarWorks@UMass AmherstInternational Conference on Engineering andEcohydrology for Fish PassageInternational Conference on Engineering andEcohydrology for Fish Passage 2014Jun 10th, 11:20 AM - 11:40 AMAn approach to model swimming behavior ofsmolts in the forebay of hydro damsA. AmadoUniversity of Wisconsin - MadisonFollow this and additional works at: https://scholarworks.umass.edu/fishpassage_conferenceThis Event is brought to you for free and open access by the Fish Passage Community at UMass Amherst at ScholarWorks@UMass Amherst. It hasbeen accepted for inclusion in International Conference on Engineering and Ecohydrology for Fish Passage by an authorized administrator ofScholarWorks@UMass Amherst. For more information, please contact scholarworks@library.umass.edu.Amado, A., "An approach to model swimming behavior of smolts in the forebay of hydro dams" (2014). International Conference onEngineering and Ecohydrology for Fish Passage. 23.https://scholarworks.umass.edu/fishpassage_conference/2014/June10/23AN APPROACH TO MODEL SWIMMING BEHAVIOR OF SMOLTS IN THE FOREBAY OF HYDRO DAMS       Antonio Arenas Amado  Marcela Politano Larry Weber  Mark Timko  1 2 Introduction and Research Questions  Understanding juvenile salmon swimming patterns can assist in: - Conducting fish survival studies - Assessing fish bypass efficiency - Designing diversion structures - Defining spillway and powerhouse operating conditions - Estimating Total Dissolved Gas (TDG) exposure - Meeting regulations  Currently, acoustic tags are commonly used to monitor fish behavior as they approach hydropower dams.   Is there a way to use measured fish behavior to make fish behavior predictions under flow conditions different from those present when fish behavior was measured?  Is there a way to use measured fish behavior to make fish behavior predictions at locations different from the site where fish behavior was studied?        3 Conceptual Model  Flow fieldinformationModel developed                in this thesisFish swimming    direction and thrustAnalysis of juvenile salmon measured trajectoriesand CFD simulationsProbability distributions and model thresholdsModel DevelopmentModel ApplicationFish behavior laboratory studiesF ma=∑ Lateral line detection capabilitiesFish muscle power output CFD simulationsF ma=∑ 4 Study Area and Flow Conditions  2005214.6#1 340.5#2 337.7#3 293.9#4 277.7#5 276.4#6 207.9#7 197.3#8 217.3#9 182.8#10 146.3#11 80.7Total 2558.5#1 0.0#2 102.8#3 0.0#4 101.9#5 136.7#6 168.3#7 135.6#8 0.0#9 0.0#10 0.0#11 0.0#12 0.0Total  645.3In 161.6Return 155.23210.2RRDFB Level (m)PowerhouseSpillwaySCRiver2007 2008148.1 148.0#1 473.5 345.1#2 437.6 389.2#3 450.3 398.1#4 457.6 390.6#5 448.6 424.9#6 434.9 376.3#7 430.6 383.7#8 432.2 384.3#9 430.0 368.6#10 453.7 385.5Total 4449.2 3846.4#1 0.0 0.0#2 0.0 0.0#3 0.0 0.0#4 0.0 0.0#5 0.0 0.0#6 0.0 0.0#7 0.0 0.0#8 0.0 0.0#9 0.0 0.0#10 0.0 0.0#11 0.0 0.0#12 0.0 0.0#13 0.0 0.0#14 0.0 0.0#15 0.0 0.0#16 0.0 0.0#17 0.0 0.0#18 0.0 0.0#19 182.1 181.9#20 182.1 181.9#21 0.0 209.6#22 0.0 20.8Total  364.2 594.14813.4 4440.5FB Level (m)PowerhouseSpillwayRiverPRD5 Measured Swim Paths  Number of swim paths Ch: 401 Sk:243 St:616 Fish positions Ch: 63,465 Sk:27,752 St: 450,374 outcome 6 Balance of Forces  fTf Ddum F Fdt= + Fish massFish velocityFish relative velocityDrag forceFish ThrustDrag coefficientRe Reynolds numberFish lengthffrfDTdffmuuFFCL========( )20.9223140.2493.9                                if  Re >2000 ReIf swimmingRe24 1 Re   if  Re 2000   Re Re0.072If gliding       Reffb ss fdf s sfbbC b     + + ≤=   +   0.5 rf rfD dfF u u ACρ= −  Re rff u Lρ µ=1) 2) 3) 4) 7 Results  8 Results  9 Distributions  10 FMM Formulation Overview  - The fish movement model (FMM) proposed is tailored to simulate downstream migrating juvenile salmon swim paths - Parameters are based on observed and measured juvenile salmon behavior - Parameters are represented by probability distributions - FMM focuses on the resultant thrust exerted by fish  - Coasting activity is included in the model - Away from obstacles, simulated fish select a swimming direction referenced to the water velocity vector - FMM is based on flow acceleration values - High flow accelerations trigger avoidance behavior - Obstacle avoidance is accomplished using the detection distance concept     11 FMM Simplified Flow Chart         flowacceleration?coasting   ?for how long, ,TF θ α1 1,i if fu x+ +no  ?for how long1 1,i if fu x+ +yes       TF Thrust magnitudeand define the thrust directionθ α=momentummomentum12 Simulated Swim Paths   Initial particle distribution Four selected Sockeye simulated swim paths. Flow conditions in PRD in 2007 13 Residence Time   14 Final Exit   M S M S M SBypass 8.5 13.0 12.0 11.9 11.5 18.7 13.8Powerhouse 91.5 87.0 88.0 88.1 88.5 81.3 86.2Passive ParticlesSteelheadSockeyeChinook15 Conclusions and Final Remarks   - Good agreement between measured and predicted final exits for Chinook could be an indication that the model is a useful tool to “transfer” measured fish behavior from one dam to another. It also suggests the existence of universal relations between fish behavior and hydrodynamics     - Model predictions capture fish final exit and residence time general trends  - The proposed methodology could also be used to simulate fish reactions to other stimuli like temperature, total dissolved gas, light, and sound   - Other variables can be included in the formulation of the model, such as temperature, time of the day, food availability, and predator abundance  - In the current model formulation simulated fish behavior is not influenced by antecedent flow conditions. Distributions given current and past flow conditions can be developed  - By averaging flow conditions over several days, local flow conditions that can trigger fish reactions can be overlooked    16 Acknowledgments  Chelan County PUD and Grant County PUD provided the measured swim paths   Dr. Eva Enders shared data on smolt avoidance behavior   17 QUESTIONS & COMMENTS 

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An approach to model swimming behavior of smolts in the forebay of hydro dams

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