A three-dimensional Lagrangian particle tracking model for predicting transport of eggs of rheophilic-spawning carps in turbulent rivers

Geng Li, Binbin Wang, Caroline M. Elliott, Bruce C. Call, Duane C. Chapman and Robert B. Jacobson

Ecological Modelling, 2022, vol. 470, issue C

Abstract: Grass carp, bighead carp, and silver carp spawn in flowing water. Their eggs, and then larvae, develop while drifting. Hydraulic conditions and water temperature control spawning locations, egg survival, and the downstream distance traveled before the hatched larvae can swim for low velocity nursery habitats. Existing egg drift models simulate the fluvial transport of carp eggs but have limitations in capturing the effect of localized turbulence on egg transport due to inadequate dimensions of hydrodynamics and/or empirical parameterization of river dispersion. We present a three-dimensional Lagrangian particle tracking model that uses fully resolved river hydrodynamics and a continuous random walk algorithm driven by local turbulent kinetic energy and its dissipation rate. We incorporate a new set of equations to compute evolving egg characteristics with fully resolved 3-D hydrodynamics. To demonstrate the performance of the model, we conducted a case study in an eight-kilometer reach of the Missouri River at the discharge of approximately 25% daily flow exceedance. Three-dimensional river hydrodynamics was modeled, calibrated, and evaluated with measurement data. Egg drift was modeled and compared using fully three-dimensional, depth-averaged two-dimensional, and zone-averaged one-dimensional hydrodynamics. The comparison shows a generally good agreement among models of downstream egg transport due to advection but a different dispersion pattern of eggs in the river, as a result of turbulent diffusion and shear induced dispersion.

Keywords: Invasive carp; Turbulence; Egg drift; River (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:470:y:2022:i:c:s0304380022001454

DOI: 10.1016/j.ecolmodel.2022.110035

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