Modeling the influence of flow on invertebrate drift across spatial scales using a 2D hydraulic model and a 1D population model

Abstract

a b s t r a c tMethods for creating explicit links in environmental flow assessments between changes in physical habitat and the availability and delivery rate of macroinvertebrates that comprise fish diets are generally lacking. Here, we present a hybrid modelling approach to simulate the spatial dynamics of macroinvertebrates in a section of the Merced River in central California, re-engineered to improve the viability of Chinook salmon. Our efforts focused on quantifying the influence of the hydrodynamic environment on invertebrate drift dispersal, which is a key input to salmon bioenergetics models. We developed a twodimensional hydrodynamic model that represented flow dynamics well at baseflow and 75% bankfull discharges. Hydraulic predictions from the 2D model were coupled with a particle tracking algorithm to compute drift dispersal, where the settling rates of simulated macroinvertebrates were parameterized from the literature. Using the cross-sectional averaged velocities from the 2D model, we then developed a simpler 1D representation of how dispersal distributions respond to flow variability. These distributions were included in 1D invertebrate population models that represent variability in drift densities over reach scales. Dispersal distributions in the 2D simulation and 1D representation responded strongly to spatial changes in flow. When included in the 1D population model, dispersal responses to flow 'scaled-up' to yield distributions of drifting macroinvertebrates that showed a strong inverse relationship with flow velocity. The strength of the inverse relationship was influenced by model parameters, including the rate at which dispersers settle to the benthos. Finally, we explore how the scale of riffle/pool variability relative to characteristic length scales calculated from the 1D population model can be used to understand drift responses for different settling rates and at different discharges. We show that, under the range of parameter values explored, changes in velocity associated with transitions between riffles and pools produce local changes in drift density of proportional magnitude. This simple result suggests a means for confronting model predictions against field data.

Causes and consequences of invertebrate drift in running waters: from individuals to populations and trophic fluxes

“…For instance, it is conceivable that drift production is relatively uniform among habitat types and spatial variation in concentration is primarily driven by heterogeneity in transport and exit dynamics (e.g., Anderson et al 2013). Empirically, flume experiments and a small number of field observations have given limited insights into transport and exit rates (e.g., Lancaster et al 1996).…”

Estimation of Transport Trajectory and Residence Time in Large River–Lake Systems: Application to Poyang Lake (China) Using a Combined Model Approach

“…(2) The purpose of the simulation using an average settling velocity (chosen to be 0.0082 m/s; Table 1) to investigate the transport behaviors of the released pollutants. However, a faster settling velocity for the particles has been tested to examine shorter transport distances than the average settling velocities of the present simulation [24,44]. (3) It should be noted that although the dispersion coefficient changes with time and location (this is the same as the flow velocity), flow velocity changes may play a considerably larger role than the variable dispersion coefficient for pollutant transport [49,50].…”

“…Forecasting the effects of flow on transport behaviors is an increasingly important objective for many river-lake systems, due to the substantial influences of flow on the water quality and associated ecosystem of the lakes [44]. Previous model studies mainly used physically based hydrodynamic models to explore the flow features of river-lake systems.…”

“…The settling velocity (ωs) and dispersion coefficients (DH and DV) have been shown to be the key parameters affecting the pattern of drift transport in the transport and particle-tracking sub-models of MIKE 21. The physical parameters in Table 1 were prescribed based on extensive literature survey of published studies in Poyang Lake [28,43] and other similar areas [38,39,44,45]. …”

Advances in Integrated Vehicle Thermal Management and Numerical Simulation

“…Because a small change in the initial conditions could have impact the output results of the 3D simulation, a validation as needed for the initial boundary conditions, but in the co-simulation study, a boundary condition exchange between 1D and 3D models can eliminate this problem. As the conventional CFD analysis for underhood thermal management for ICEV is quite time-consuming because of the complex geometry and flow distributions, the alternative of 1D/3D co-simulation for a full-scale model was introduced to reduce the analysis and design cycle time [182][183][184].…”