Abstract
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.