###### Abstract  
River meanders form complex 3D flow patterns, including secondary flows and flow separation. In particular, the flow separation traps solutes and delays their transport via storage effects associated with recirculating flows. The simulation of the separated flows highly relies in the performance of turbulence models. Thus, these closure schemes can control dispersion behaviors simulated in rivers. This study performs 3D simulations to quantify the impact of the turbulence models on solute transport simulations in channels under different sinuosity conditions. The 3D Reynolds-averaged Navier-Stokes equations coupled with the \(k-\varepsilon\), \(k-\omega\) and SST \(k-\omega\) models are adopted for flow simulations. The 3D Lagrangian particle-tracking model simulates solute transport. An increase in sinuosity causes strong transverse gradients of mean velocity, thereby driving the onset of the separated flow recirculation along the outer bank. Here, the onset and extent of the flow separation are strongly influenced by the turbulence models. The \(k-\varepsilon\) model fails to reproduce the flow separation or underestimates its size. As a result, the \(k-\varepsilon\) model yields residence times shorter than those of other models. In contrast, the SST \(k-\omega\) model exhibits a strong tailing of breakthrough curves by generating more pronounced flow separation. m 20202015 April 202016 April 2020  
(DNS) [8; 9; 10; 11]. The main advantage of the LES model is that the near-bank secondary flow within the channel bend is superiorly reproduced compared to the RANS model [12; 13]. The previous experimental studies; however, reported that the near-bank cell shrinks as the Froude number increases [14] and possesses relatively weaker strength and smaller size than those of the main secondary flow cell at the central regions [15]. Therefore, in consideration of computational efficiency, the RANS model is an acceptable alternative for computing large-scale flow structures and shear flow dispersion accordingly in meandering channels. The flow structures simulated with the 3D RANS model substantially rely on turbulence models. Among several turbulence models, two-equation models are widely used for flow analysis. Since the research of [PERSON] and [PERSON] [16], the \(k-\varepsilon\) model has widely been employed for hydrodynamic simulations in meander bends due to the computational stability with good convergence, adequately capturing entire flow patterns of the secondary circulations [17; 18; 19; 20]. However, the \(k-\varepsilon\) model often fails to reproduce the adverse pressure gradient flows, thus causing inaccurate results in boundary layer flows [21]. The \(k-\omega\) model overcomes the disadvantages of the \(k-\varepsilon\) model by achieving more precise simulations in the wall boundary layers under the adverse pressure gradient conditions [22]. Yet, both the \(k-\varepsilon\) and \(k-\omega\) models lack the ability to reproduce massively separated flows under severe adverse pressure gradients [23; 24]. As an alternative to these turbulence models, [PERSON] [25] proposed the shear stress transport (SST) \(k-\omega\) model, which combines the robust formulations of the \(k-\omega\) model for the near-wall regions and the \(k-\varepsilon\) model for the free-flow regions. The SST \(k-\omega\) model has been shown to accurately predict the onset and extent of the flow separation in complex geometric configurations [26; 27; 28]. In rivers and streams, the flow separation is frequently observed owing to the intricate flow patterns associated withomorphic features of rivers, such as confluence, pool-riffle sequence, bifurcation, and meander [29; 30]. Notably, the experimental studies of [PERSON] [31; 32; 33] revealed that sharp channel curvature forms a pronounced flow separation near the bend apex because of significant adverse pressure gradients, and this curvature-induced flow separation manifests as a recirculation zone in the horizontal plane.