Hydrodynamics of river-channel confluence: toward modeling separation zone using GEP, MARS, M5 Tree and DENFIS techniques

Hydrodynamics of confluence as a natural component in river-channel networks is complicated. Having sufficient knowledge about erosion and sedimentation in the river-channel confluences requires determination of the separation zone dimensions. In this paper, we estimated dimension of separation zone (i.e. length and width) by utilizing data driven techniques: gene expression programming (GEP), M5 Tree model, multivariate adaptive regression spline (MARS), and dynamic evolving neural-fuzzy inference system (DENFIS) trained with hydraulics input variables including discharge ratio (Q r ), downstream Froude number (Fr 3 ), and side slope angle of main channel ( sin θ ). Different splitting scenarios, 50–50