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[1] River confluences are complex hydrodynamic environments where convergence of incoming flows produces complicated patterns of fluid motion, including the development of large-scale turbulence structures. Accurately simulating confluence hydrodynamics represents a considerable challenge for numerical modeling of river flows. This study uses an eddy-resolving numerical model to simulate the mean flow and large-scale turbulence structure at an asymmetrical river confluence with a concordant bed when the momentum ratio between the two incoming streams is close to 1. Results of the simulation are compared with field data on mean flow and turbulence structure. The simulation shows that the mixing interface is populated by quasi-two-dimensional eddies. Successive eddies have opposing senses of rotation. The mixing layer structure resembles that of a wake behind a bluff body (wake mode). Strong streamwise-oriented vortical (SOV) cells form on both sides of the mixing layer, a finding consistent with patterns inferred from the field data. The predicted mean flow fields show that flow curvature has an important influence on streamwise variation of circulation within the cores of the two primary SOV cells. These SOV cells, along with vortices generated by flow over a submerged block of sediment at one of the banks, strongly influence distributions of the streamwise velocity and turbulent kinetic energy downstream of the junction. Comparison of the eddy-resolving simulation results with predictions from the steady Spalart-Allmaras RANS model shows that the latter fails to predict important features of the measured distributions of streamwise velocity and turbulent kinetic energy because the RANS model underpredicts the strength of the SOV cells. Analysis of instantaneous and mean bed shear stress distributions indicates that the SOV cells enhance bed shear stresses to a greater degree than the quasi-two-dimensional eddies in the mixing interface.

The flow and turbulence structure at stream confluences are characterized by the formation of a mixing interface (MI) and, in some cases, of streamwise‐oriented vortical (SOV) cells flanking the MI. Depending on the junction angle and planform symmetry, as well as the velocity ratio across the MI, the MI can be in the Kelvin‐Helmholtz (KH) mode or in the wake mode. In the former case, the MI contains predominantly co‐rotating large‐scale quasi two‐dimensional (2‐D) eddies whose growth is driven by the KH instability and vortex pairing. In the latter case, the MI is populated by quasi 2‐D eddies with opposing senses of rotation. This study uses eddy resolving simulations to predict details of flow structure for KH‐ and wake‐mode conditions at a confluence for which field measurements are available. Results indicate that SOV cells at this confluence, which occur in both modes, redistribute momentum and mass, enhancing the potential for entrainment of bed material beneath the cells and for extraction of fluid and suspended sediment from the MI. The simulations predict that the cores of some of the primary SOV cells are subject to large‐scale bimodal oscillations toward and away from the MI that contribute to amplification of the turbulence close to the MI and enhance the capacity of the SOV cells to entrain sediment. At this confluence, which has a concordant bed and a large angle between the incoming streams ‐ conditions that generate strong adverse lateral pressure gradients adjacent to the MI ‐ the oscillating SOV cells interact with MI eddies to generate large bed friction velocities in the zone of scour immediately downstream of the confluence.

Abstract. Stream confluences are among the most highly turbulent locations in fluvial systems. This paper examines the three-dimensional structure of turbulence at three stream confluences in east central Illinois. The analysis focuses on the characteristics of turbulence both within the shear layer and in the ambient flow. Results show that at the upstream end of each confluence the shear layer occupies a limited portion of the flow cross-sectional area, but turbulence kinetic energy within this layer is 2-3 times greater than the turbulence kinetic energy of the ambient flow, which has turbulence characteristics similar to those for flow in straight channels. Turbulence within the shear layer can be characterized as quasi-two-dimensional in the sense that large-scale turbulence generated by transverse shear is predominantly two dimensional, whereas small-scale turbulence associated with bed friction is three dimensional. Spectral analysis suggests that the structure of fluid motion within the shear layer differs for confluences with symmetrical versus asymmetrical planforms. The shear layer dissipates rapidly as flow enters the downstream channel, even though a well-defined mixing interface persists at downstream locations.

Moving sand waves and the overlying tubulent flow were measured on the Wilga River in Poland, and the Tirnava Mica and Buzau Rivers in Romania. Bottom elevations and flow velocities were measured at six points simultaneously by multi-channel measuring systems. From these data, the linear and two-dimensional sections of the three-dimensional correlation and structure functions and various projections of sand wave three-dimensional spectra were investigated.It was found that the longitudinal wavenumber spectra of the sand waves in the region of large wavenumbers followed Hino's −3 law (S(Kx) ∝K−3x) quite satisfactorily, confirming the theoretical predictions of Hino (1968) and Jain & Kennedy (1974). However, in contrast to Hino (1968), the sand wave frequency spectrum in the high-frequency region was approximated by a power function with the exponent −2, while in the lower-frequency region this exponent is close to −3.A dispersion relation for sand waves has been investigated from analysis of structure functions, frequency spectra and the cross-correlation functions method. For wavelengths less than 0.15–0.25 of the flow depth, their propagation velocity C is inversely proportional to the wavelength λ. When the wavelengths of spectral components are as large as 3–4 times the flow depth, no dispersion occurs. These results proved to be in good qualitative agreement with the theoretical dispersion relation derived from the potential-flow-based analytical models (Kennedy 1969; Jain & Kennedy 1974). We also present another, physically-based, explanation of this phenomenon, introducing two types of sand movement in the form of sand waves. The first type (I) is for the region of large wavenumbers (small wavelengths) and the second one (II) is for the region of small wavenumbers (large wavelengths). The small sand waves move due to the motion of individual sand particles (type I, C∝λ−1) while larger sand waves propagate as a result of the motion of smaller waves on their upstream slopes (type II, C∝λ0). Like the sand particles in the first type, these smaller waves redistribute sand from upstream slopes to downstream ones. Both types result in sand wave movement downstream but with a different propagation velocity.The main characteristics of turbulence, as well as the quantitative values characterizing the modulation of turbulence by sand waves, are also presented.