Sediment transport due to fluid motion is a crucial process in many environmental and engineered systems. Therefore, understanding sediment transport is critical for predicting sediment movements and evaluating the short and/or long-term influence to the surface water systems. Despite the importance of sediment transport, the fundamental aspects involved are far from being completely understood. At the core of the problem is the complex interaction between a turbulent flow field and sediment particles. In this sense, for sediment transport modelling, how to account for as many turbulence generation or destruction mechanisms as possible is one of the keys to improving the accuracy of prediction. The most widely used and validated model for turbulence is two-equation k-e model. However, the traditional k-e model cannot provide accurate predictions when considering the presence of sediment in water due to missing the terms in the equations that can account for energy transfer between sediments and turbulence, as well as the terms for inter-particle interactions. Moreover, the standard k-e model is only valid for fully developed turbulent flow, so it often has difficulties to deal with near-bottom layer (e.g. low-Reynolds effects and high sediment concentrations). Therefore, an alternative approach to overcome these difficulties is two-phase flow theory. In the first part of this study, a modified two-equation k-e model with additional turbulence modulation terms, accounting for the influence of particles on the turbulent flow field, has been proposed. These extra terms are derived using a two-phase flow approach. In the numerical tests, the modified two-phase k-e model reproduces the features of turbulence modulation observed in the experiments on sediment-laden flow. Another important aspect in sediment transport is the treatment of the near-bottom layer. It has been hypothesized for more than a decade that currently used sediment transport models for morphodynamic studies (e.g., harbour siltation, system response ...