Studies on turbulent diffusion processes and evaluation of diffusivity values from hydrodynamic observations in Corpus Christi Bay

Ojo, Temitope; Bonner, James S.; Page, Cheryl

doi:10.1016/j.csr.2006.08.007

Cited by 5 publications

(4 citation statements)

References 28 publications

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“…Previously, data measured by various submersible sensors were acquired and visualized in real time through the Multi-Parameter Instrument Array and Control System (MPIACS) software developed in our research group (Ojo et al 2006(Ojo et al , 2007b. It displayed horizontal variation of intensities of the measured parameters (measured value relative to a pre-set peak value) along the transect route and thereby aided in selecting the transect route 'on the fly' to capture the horizontal extent of the parameters of interest.…”

Section: Mobile Monitoring Systemmentioning

confidence: 99%

“…Considering its impact to the economy, the National Estuary Program designated Corpus Christi (CC) Bay as a National Estuary in 1992 and created the Corpus Christi Bay National Estuary Program to protect the health of this bay while supporting its economic growth. This enclosed shallow bay is wind-driven and so can be described as a highly pulsed system (Ojo et al 2006). It cycles through various episodic events such as sediment resuspension, flooding, water column stratification, and hypoxia.…”

Section: Introductionmentioning

confidence: 99%

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A mobile monitoring system to understand the processes controlling episodic events in Corpus Christi Bay

Islam¹,

Bonner²,

Ojo³

et al. 2010

Environ Monit Assess

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Corpus Christi Bay (TX, USA) is a shallow wind-driven bay and thereby, can be characterized as a highly pulsed system. It cycles through various episodic events such as hypoxia, water column stratification, sediment resuspension, flooding, etc. Understanding of the processes that control these events requires an efficient observation system that can measure various hydrodynamic and water quality parameters at the multitude of spatial and temporal scales of interest. As part of our effort to implement an efficient observation system for Corpus Christi Bay, a mobile monitoring system was developed that can acquire and visualize data measured by various submersible sensors on an undulating tow-body deployed behind a research vessel. Along with this system, we have installed a downward-looking Acoustic Doppler Current Profiler to measure the vertical profile of water currents. Real-time display of each measured parameter intensity (measured value relative to a pre-set peak value) guides in selecting the transect route to capture the event of interest. In addition, large synchronized datasets measured by this system provide an opportunity to understand the processes that control various episodic events in the bay. To illustrate the capability of this system, datasets from two research cruises are presented in this paper that help to clarify processes inducing an inverse estuary condition at the mouth of the ship channel and hypoxia at the bottom of the bay. These measured datasets can also be used to drive numerical models to understand various environmental phenomena that control the water quality of the bay.

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Section: Mobile Monitoring Systemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A mobile monitoring system to understand the processes controlling episodic events in Corpus Christi Bay

Islam¹,

Bonner²,

Ojo³

et al. 2010

Environ Monit Assess

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“…In shallow, nearshore areas of the Great Lakes where circulation is primarily wind‐driven, the velocity gradients responsible for producing shear are larger in the vertical compared to those in the horizontal plane. This shear‐augmented diffusion was investigated by [ Ojo et al ., , ] and quantified for the Corpus Christi Bay, Texas using ADCP measurements. They found that shear‐augmented diffusion can dominate turbulent mixing in shallow estuarine waters producing effective mixing rates that are 10 to 20 times higher than estimates based on turbulence alone.…”

Section: Introductionmentioning

confidence: 99%

Solute dispersion in the coastal boundary layer of southern Lake Michigan

2013

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[1] We evaluate a three-dimensional, nested-grid nearshore model of Lake Michigan for its ability to describe key aspects of hydrodynamics and solute transport using data from a field study conducted in summer 2008. Velocity comparisons with observations from five bottom-mounted ADCPs at different depths in the coastal boundary layer (CBL) show that the numerical model was able to simulate currents and flow reversals accurately within the inertial boundary layer, however model accuracy reduced close to the shoreline. Power spectra of observed and simulated velocity time series at different locations showed that the hydrodynamic model was able to describe the energy contained in the inertial scales, but over-predicted turbulent dissipation rates. As a result, model-predicted values of energy in the smaller, dissipation scales were lower compared to values calculated from observations in the CBL. Differences between energy contained in the observed and simulated velocity spectra increased as the shoreline is approached. Observations showed that vertical variations in the alongshore and cross-shore velocities were dominated by inertial waves. Inaccuracies in representing energy dissipation rates and processes not explicitly described in the hydrodynamic model (e.g., anisotropy, waves) could potentially contribute to errors in describing transport in the CBL. Measurements from a continuous dye release experiment from a riverine outfall were described using a nearshore model with a mean horizontal dispersion coefficient of 5.6 m 2 /s. Improved representations of physical processes (such as turbulence, internal waves and wave-current interactions) can be expected to provide better descriptions of solute transport in the CBL.

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“…Ojo et al [15] conducted several dye study experiments in CC Bay and found the significant variation in the spatial distribution of the dispersion coefficient within the bay. This difference in the vertical dispersion coefficient may be more pronounced during the stratified condition when there is a greater probability of the occurrence of hypoxia in the bay.…”

Section: Description Of the Model Developmentmentioning

confidence: 99%

A mechanistic dissolved oxygen model of Corpus Christi Bay to understand critical processes causing hypoxia

et al. 2008

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Abstract-Corpus Christi Bay (TX, USA) is a shallow wind-driven bay which experiences hypoxia (dissolved oxygen<2 mg/L) during the summer months in the southeast region of the bay. We have developed and installed real-time monitoring systems in the bay to measure various water quality, meteorological and hydrodynamic parameters. These systems can aid in determining the extent and frequency of hypoxic events in this energetic bay. A three-dimensional mechanistic dissolved oxygen model has been developed in this study to investigate the key processes that induce hypoxia in Corpus Christi (CC) Bay. This model includes variable advection and dispersion coefficients so that it can be driven by real-time monitoring hydrodynamic data. The results from model simulations indicate that hypoxia may occur at the lower depths of the bay when both stratification and higher biological activity conditions exist. The water column in the south-east part of the bay becomes stratified during calm wind conditions when there is inflow of hyper-saline water from the neighboring Laguna Madre waterbody. This condition, when combined with higher biological activity during the summer months, induces hypoxia at the lower depths of the bay. The simulation results also point out that physical transport processes have more pronounced effect on the DO distribution within the water column than the effects of biological activity. Therefore, it is necessary to develop suitable sampling strategies that will measure hydrodynamic data at greater spatial and temporal resolution. The integration of this data with our developed model will provide a useful tool to the stakeholders to assess the water quality of the bay in real time.

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Studies on turbulent diffusion processes and evaluation of diffusivity values from hydrodynamic observations in Corpus Christi Bay

Cited by 5 publications

References 28 publications

A mobile monitoring system to understand the processes controlling episodic events in Corpus Christi Bay

A mobile monitoring system to understand the processes controlling episodic events in Corpus Christi Bay

Solute dispersion in the coastal boundary layer of southern Lake Michigan

A mechanistic dissolved oxygen model of Corpus Christi Bay to understand critical processes causing hypoxia

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