Many aquatic environments are dominated by muddy sediments. These cohesive sediments, however, often contain a mixture of sand, mud and organic material, giving rise to complex interactional behaviour, the nature of which is often controlled by bio-physical attributes. An understanding of these complex interactions is paramount in the accurate prediction of sediment transport processes in numerical models, facilitating monitoring and management of marine environments. Calibration of such models relies on quantitative erodibility and depositional data. Muddy sediments flocculate; a process impacted by complex sedimentary and hydrodynamic interactions. The degree of sediment stability describes the degree of flocculation and depends on interactive forces (including bonding cohesion) between suspended particulate matter and turbulent shear stress, as well as mineralogy and biological composition. Erodibility and deposition properties rely greatly on the formation and break-up of these flocs, in turn impacting processes of sediment transport. This study examines, through the use and comparison of various data sets, aspects of both erodibility and deposition for several different sedimentary conditions. Collation of a range of quantitative field and laboratory-derived sedimentary and hydrodynamical data sets (e.g. sediment composition, floc properties, bed density, mass erosion rates, erosion thresholds, suspended particular matter concentration, turbulent shear stress) from a range of aquatic scenarios (including estuaries, intertidal areas, shelf seas, and lakes) are utilised to investigate the impacts of related controlling and influencing parameters on sediment transport, in particular to assess coastal erosion and sustainability. Case studies include: water quality monitoring, contaminated sediments, and dredging applications; these will be used to demonstrate / illustrate various applications of this sedimentary-hydrodynamic investigation. This research augments our understanding of the interactive processes within different cohesive sediments, providing quantitative analysis to inform and ultimately improve our mathematical representation of bio-physical sedimentary processes for implementation within predictive numerical modelling.