Water quality in river systems is an important issue, and relies on various factors including our ability to predict how effluents from outfalls mix with river water. However, predicting mixing in rivers, and especially in river bends, remains a difficult problem to solve. The goal of this project is to develop a comprehensive picture of the mixing mechanisms of an effluent jet in a river bend. This is done with experiments in both bend flumes in the University of Ottawa Water Resources Engineering Laboratory. The large bend flume is 1 m in width, and contains a single 135° bend of radius 1.5 m, and the small flume has a channel width of 0.2 m with a 135° bend of radius 0.3 m. The experiments in the large flume used acoustic Doppler velocimeters to measure velocity, and the experiments in the small flume used particle image velocimetry to track flow fields. Large eddy simulation (LES) were also completed using the same channel geometry as the small flume. To complete the parametric analysis on mixing of a neutrally buoyant effluent jet in a channel bend, 35 flow conditions, from seven channel aspect ratios and five momentum ratios, are modelled using LES. Each flow condition is also modelled without the jet present. Particle image velocimetry data from the small bend flume validates the LES models. Additionally, acoustic Doppler velocimeter tests were completed in the large bend flume under two different flume flow rates, two jet flow rates, and two aspect ratios. These models and measurements provide a broad range of the parameters under investigation. The experiments in the large bend flume establish the shape of the jet's trajectory within the channel bend, and how it differs from a trajectory in a straight crossflow. From these experiments, it is established that the centre position of the secondary circulation cell is an important parameter for determining the position of the jet. Through the LES models, more details of the 3D velocity and effluent distributions are available, allowing for a detailed analysis of how the secondary circulation develops and how the jet vortices change the development patterns. A method for clustering instantaneous vortices to separate sub-cells of secondary circulation is established, and is used to set a baseline for the development of secondary flow in a channel bend without a jet. The effect of an added jet was investigated in detail for a single flow condition, and then with machine learning techniques to develop a parametrical model incorporating both channel and jet flow conditions. The best performing machine learning model for the parametrisation of secondary flow cells with the jet is the ANFIS model coupled with a decision tree classifying the presence of each sub-cell; without the jet, the best-performing model is the ANFIS model without any additional classification. The effluent distribution is well-characterised using multiple linear regression. The addition of a jet changes the relative strengths of secondary circulation sub-cells and their circulation development and retention characteristics, though the total circulation in the bend is not strongly affected by the jet.