Flooding in a river is a complex phenomenon which affects the livelihood and economic condition of the region. During flooding flow overtops the river course and spreads around the flood plain resulting in a two-course compound channel. It has been observed that the flow velocity in the flood plain is slower than that in the actual river course. This can produce a large shear layer between sections of the flow and produces turbulent structures which generate extra resistance and uncertainty in flow prediction. Researchers have adopted various numerical, analytical, and empirical models to analyze this situation. Generally, a one-dimensional empirical model is used for flow prediction assuming that the flow in the compound open channel is uniform. However, flow in a compound channel is quasi-uniform due to the transfer of momentum in sub-sections and sudden change of depths laterally. Hence, it is essential to analyze the turbulent structures prevalent in the situation. Therefore, in this study, an effort has been made to analyze the turbulent structure involved in flooding using large eddy simulation (LES) method to estimate the resistance. Further, a combination of an artificial neural network (ANN) and a fuzzy logic (FL) is considered to predict flow resistance in a compound open channel.