Matthew D. Rayson

Time scales in Galveston Bay: An unsteady estuary

Estuarine time scales including the turnover, particle e-folding time, the age (calculated with a passive tracer), and residence time (calculated with Lagrangian particles) were computed using a three-dimensional hydrodynamic model of Galveston Bay, a low-flow, partially stratified estuary. Time scales were computed during a time period when river flow varied by several orders of magnitude and all time scales therefore exhibited significant temporal variability because of the unsteadiness of the system. The spatial distributions of age and residence time were qualitatively similar and increased from 15 days in a shipping channel to >45 days in the upper estuary. Volume-averaged age and residence time decreased during high-flow conditions. Bulk time scales, including the freshwater and salinity turnover times, were far more variable due to the changing river discharge and salt flux through the estuary mouth. A criterion for calculating a suitable averaging time is discussed to satisfy a steady state assumption and to estimate a more representative bulk time scale. When scaled with a freshwater advective time, all time scales were approximately equal to the advective time scale during high-flow conditions and many times higher during low-flow conditions. The mean age, Lagrangian residence, and flushing times exhibited a relationship that was weakly dependent on the freshwater advective time scale demonstrating predictability even in an unsteady, realistic estuary.

Combining deterministic modelling with artificial neural networks for suspended sediment estimates

The presented manuscript presents a novel approach to the applied ocean and coastal engineering problem of sediment concentration estimates.The approach has been developed on the basis of numerical modelling and with application of artificial neural networks.It has been demonstrated that the proposed methodology can be generalised onto near-by locations.Further generalisation must be tested before applying. Estimates of suspended sediment concentrations and transport are an important part of any marine environment assessment study because these factors have a direct impact on the life cycle and survival of marine ecosystems. This paper proposes to implement a combined methodology to tackle these estimates. The first component of the methodology comprised two numerical current and wave models, while the second component was based on the artificial intelligence technique of neural networks (ANNs) used to reproduce values of sediment concentrations observed at two sites. The ANNs were fed with modelled currents and waves and trained to produce area-specific concentration estimates. The trained ANNs were then applied to predict sediment concentrations over an independent period of observations. The use of a data set that merged together observations from both the mentioned sites provided the best ANN testing results in terms of both the normalised root mean square error (0.13) and the mean relative error (0.02).

Using an isohaline flux analysis to predict the salt content in an unsteady estuary

AbstractAn estuary is classified as unsteady when the salinity adjustment time is longer than the forcing time scale. Predicting salt content or salt intrusion length using scaling arguments based on a steady-state relationship between flow and salinity is inaccurate in these systems. We have used a time-dependent salinity box-model based on an unsteady Knudsen balance to demonstrate the effects of river flow, inward total exchange flow (tidal plus steady), and the salinity difference between inflow and outflow on the salt balance. A key component of the box-model is a relationship we present linking the normalized difference between inflowing and outflowing salinity at the mouth and the mean salinity content. We show that the normalized salinity difference is proportional to the mean salinty squared based on theoretical arguments from the literature. We demonstrate the validity of the box-model by hindcasting five years of mean salinity in Galveston Bay (estimated from coarse observations) in response to...