Long-term response and prediction of estuarine cohesive sediment transport

Introduction:

Aim: Nutrients, carbon, and contaminants are exchanged at the ocean-river interface, often via difficult-to-predict suspended particulate matter (SPM). This PhD project will improve SPM predictive capabilities of numerical models by developing and incorporating new sediment transport formulations into models and use these developments to predict cohesive sediment transport across long time-scales.

Introduction:

Estuaries are a critical interface between land and coastal ocean across which freshwater, suspended particulate matter (SPM), and consequently terrestrial carbon, nutrients and anthropogenic contaminants are exchanged. Estuarine water quality is in part mediated by its suspended particulate load, and sediments continually interact with biogeochemical processes. Estuarine hydrodynamics typically result in sediment trapping. Though a conceptual understanding of estuarine sediment transport exists, predictions of SPM concentrations and distributions remain elusive (e.g., Fitzsimmons et al., 2011), particularly at time scales of seasons and longer, and there is a pressing need for improved predictions of estuarine SPM and its transport.

Estuarine sediments include significant fractions of cohesive material, such as mud, whose transport is subject to a range of complex processes, including flocculation, hindered settling, consolidation, liquefaction, turbulence damping, and bioarmouring (Winterwerp and van Kesteren, 2004). There is a lack of simple and computationally efficient formulations unified across varying hydrodynamic regimes and seasons to describe cohesive behaviour in estuarine numerical models (e.g. Amoudry and Souza, 2011a) that can be used by coastal scientists, engineers and consultants. This project will address this critical gap and generate new process-based modelling approaches for simulations of estuarine cohesive sediment transport over time scales ranging from tides to seasons.

Project Summary:

The studentship aims to increase the predictive ability of estuarine SPM from tidal to seasonal timescales. While both physical and biological influence on cohesive behaviour are recognized, quantitative assessment of their relative importance across time scales remains uncertain. The project will seek to address the following (non-exhaustive) research questions: How do physical and biological processes combine to control cohesive sediment response across time scales? How are these processes best represented in numerical models? A working hypothesis to be tested during the project is that physical processes dominate at short (up to weeks) time scales while biological processes dominate at seasonal time scales. Specific objectives will be to

derive and implement novel formulation(s) for settling rate and bed resuspension that account for both physical and biological processes
test, calibrate, and validate the model against in situ estuarine observations in several different estuarine environments
identify and quantify dominant mechanisms controlling transport of estuarine cohesive sediments across time scales

The studentship will focus on deriving novel expressions for resuspension, deposition and settling rates following analyses of observational data, which may involve the use of new machine learning techniques, and implementing them in a state-of-the-art coastal ocean community modelling system.

The studentship will combine use of in-situ observations and three-dimensional baroclinic modelling. The project will build upon previous studies in the Dee Estuary and upon ongoing research through the BLUEcoast project, a consortium led by NOC investigating the role of physical and biological processes on coastal evolution and recovery. Available datasets collected in the Dee Estuary span several years and seasons providing a unique opportunity to holistically address longer timescales in this estuary. Each dataset offers comprehensive month-long observations of cohesive and mixed sediment transport processes, including measurements of SPM size, near-bed currents and turbulence, full water column hydrodynamics, and near-bed sand transport. These data will be complemented by new similarly comprehensive data to be collected in two other estuarine environments (Blackwater and Morecambe Bay) within BLUEcoast in 2017 and 2018.

Work plan:

Research training: critical review of literature, familiarisation with data analysis, and numerical modelling techniques.
Development and numerical implementation of new formulations for resuspension, deposition, and settling rates.
Model testing, validation against observations, sensitivity analysis.
Synthesis: Analysis of numerical results towards determining mechanisms controlling estuarine sediment transport.
Outputs and dissemination: presentations at national and international conferences, writing reports and papers, PhD thesis.

In addition to the DTP training, the student will receive training in mathematical and physical analytical techniques, data analysis, numerical modelling, and participate in estuarine fieldwork. A strong mathematical and/or physical background and computational literacy is required. Previous exposure to coastal physical oceanography or coastal engineering is advantageous but not essential.