Salmonids create an egg nest, called a redd, in hyporheic streambed gravel to bury their eggs, characterized by a pit and a hump topography, resembling a dune. Embryos' survival depends on downwelling oxygen‐rich stream water fluxes, influenced by the redd shape, stream hydraulics, and the hydraulic conductivity of the redd sediment, K. We hypothesize that downwelling fluxes increase with stream discharge and redd aspect ratio (A_R = A/L, with A, the redd amplitude and L, its length), and they can be predicted using a set of dimensionless numbers, which include the stream flow Reynolds (Re) and Froude (Fr) numbers, A_R, and the redd relative submergence (A/Y₀, with Y₀, the water depth). We address our goal by simulating the surface and subsurface flows with numerical hydraulic models linked through the near‐bed pressure distribution quantified with a two‐phase (air‐water) two‐dimensional surface water computational fluid dynamics model, validated with experiments. We apply the modeling approach to five redd sizes, which span the field observed range (from ∼1 to ∼4 m long), and by increasing discharge from shallow (0.1 m) and slow (0.15 m/s) to deep (8 m) and fast (3.3 m/s). Results confirm that downwelling fluxes increase with discharge and redd aspect ratio due to the increased near‐bed head gradient over the redd. Averaged downwelling fluxes are a function of Re, Fr, A_R, and hydraulic conductivity of the redd and not of the undisturbed streambed material. The derived regression equation may help evaluate regulated and unregulated flow impacts on hyporheic flows during embryo incubation.

Aneurysms are localized expansions of weakened blood vessels that can be debilitating or fatal upon rupture. Previous studies have shown that flow in an aneurysm exhibits complex flow structures that are correlated with its inflow conditions. Therefore, the objective of this study was to demonstrate the application of Proper Orthogonal Decomposition (POD) to study the impact of different inflow conditions on energetic flow structures and their temporal behavior in an aneurysm. To achieve this objective, experiments were performed on an idealized rigid sidewall aneurysm model. A piston pump system was used for precise inflow control, i.e., peak Reynolds number ($Re_p$) and Womersley number ($\alpha$) were varied from 50-270 and 2-5, respectively. The velocity flow field measurements at the mid-plane location of the idealized aneurysm model were performed using Particle Image Velocimetry (PIV). The results demonstrate the efficacy of POD in decomposing complex data, and POD was able to capture the energetic flow structures unique to each studied inflow condition. Furthermore, the time-varying coefficient results highlighted the interplay between the coefficients and their corresponding POD modes, which in turn helped explain how POD modes impact certain flow features. The low-order reconstruction results were able to capture the flow evolution and provide information on complex flow in an aneurysm. The POD and low-order reconstruction results also indicated that vortex formation, evolution, and convection varied with an increase in $\alpha$, while vortex strength and formation of secondary structures were correlated with an increase in $Re_p$.

Typically, fish passage design is informed by a critical velocity model whereby fish are assumed to fail passage if the water velocity is higher than the critical swim speed, an assumption that may not be met when locomoting fish are partially submerged. We applied a drag force model (DFM) approach for use in design of Pacific Lamprey (Entosphenus tridentatus) Passage Structures (LPS) where lamprey may be partially or fully submerged. Our investigation assessed the dead-drag forces at four levels of static submergence: fully submerged (120 mm), equally submerged (40 mm), partially submerged (15 mm), and skin-flow (5 mm) for a Pacific Lamprey physical model by varying simulated LPS slope and discharge conditions. We then used the results to establish drag force thresholds corresponding to the known critical velocity thresholds of Pacific Lamprey to predict passage success under partial and full submergence conditions. Consideration of drag force in fish passage could be used to improve or create species-specific design recommendations for fishways, or to inform the design of barriers to prevent invasive species passage. The results suggest consideration of drag force in addition to velocity is beneficial to predict Pacific Lamprey passage success under partial submergence conditions.

Porous media flows are common in both natural and anthropogenic systems. Mapping these flows in a laboratory setting is challenging and often requires non-intrusive measurement techniques, such as particle image velocimetry (PIV) coupled with refractive index matching (RIM). RIM-coupled PIV allows the mapping of velocity fields around transparent solids by analyzing the movement of neutrally buoyant micron-sized seeding particles. The use of this technique in a porous medium can be problematic because seeding particles adhere to grains, which causes the grain bed to lose transparency and can obstruct pore flows. Another non-intrusive optical technique, planar laser-induced fluorescence (PLIF), can be paired with RIM and does not have this limitation because fluorescent dye is used instead of particles, but it has been chiefly used for qualitative flow visualization. Here, we propose a quantitative PLIF-based methodology to map both porous media flow fields and porous media architecture. Velocity fields are obtained by tracking the advection-dominated movement of the fluorescent dye plume front within a porous medium. We also propose an automatic tracking algorithm that quantifies 2D velocity components as the plume moves through space in both an Eulerian and a Lagrangian framework. We apply this algorithm to three data sets: a synthetic data set and two laboratory experiments. Performance of this algorithm is reported by the mean (bias error, B) and standard deviation (random error, SD) of the residuals between its results and the reference data. For the synthetic data, the algorithm produces maximum errors of B & SD = 32% & 23% in the Eulerian framework, respectively, and B & SD = −0.04% & 3.9% in the Lagrangian framework. The small-scale laboratory experimental data requires the Eulerian framework and produce errors of B & SD = −0.5% & 33%. The Lagrangian framework is used on the large-scale laboratory experimental data and produces errors of B & SD = 5% & 44%. Mapping the porous media architecture shows negligible error for reconstructing calibration grains of known dimensions.