DEVELOPMENT OF A COASTAL MARGIN OBSERVATION AND ASSESSMENT SYSTEM (CMOAS) TO CAPTURE THE EPISODIC EVENTS IN A SHALLOW BAY
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Corpus Christi Bay (TX, USA) is a shallow wind-driven bay which is designated as a National Estuary due to its impact on the economy. But this bay experiences periodic hypoxia (dissolved oxygen <2 mg/l) which threatens aerobic aquatic organisms. Development of the Coastal Margin Observation and Assessment System (CMOAS) through integration of real-time observations with numerical modeling helps to understand the processes causing hypoxia in this energetic bay. CMOAS also serves as a template for the implementation of observational systems in other dynamic ecosystems for characterizing and predicting other episodic events such as harmful algal blooms, accidental oil spills, sediment resuspension events, etc. State-of-the-art sensor technologies are involved in real-time monitoring of hydrodynamic, meteorological and water quality parameters in the bay. Three different platform types used for the installation of sensor systems are: 1) Fixed Robotic, 2) Mobile, and 3) Remote. An automated profiler system, installed on the fixed robotic platform, vertically moves a suite of in-situ sensors within the water column for continuous measurements. An Integrated Data Acquisition, Communication and Control system has been configured on our mobile platform (research vessel) for the synchronized measurements and real-time visualization of hydrodynamic and water quality parameters at greater spatial resolution. In addition, a high frequency (HF) radar system has been installed on remote platforms to generate surface current maps for Corpus Christi (CC) Bay and its offshore area. This data is made available to stakeholders in real-time through the development of cyberinfrastructure which includes establishment of communication network, software development, web services, database development, etc. Real-time availability of measured datasets assists in implementing an integrated sampling scheme for our monitoring systems installed at different platforms. With our integrated system, we were able to capture evidence of an hypoxic event in Summer 2007. Data collected from our monitoring systems are used to drive and validate numerical models developed in this study. The analysis of observational datasets and developed 2-D hydrodynamic model output suggests that a depth-integrated model is not able to capture the water current structure of CC Bay. Also, the development of a threedimensional mechanistic dissolved oxygen model and a particle aggregation transport model (PAT) helps to clarify the critical processes causing hypoxia in the bay. The various numerical models and monitoring systems developed in this study can serve as valuable tools for the understanding and prediction of various episodic events dominant in other dynamic ecosystems.
Islam, Mohammad S. (2009). DEVELOPMENT OF A COASTAL MARGIN OBSERVATION AND ASSESSMENT SYSTEM (CMOAS) TO CAPTURE THE EPISODIC EVENTS IN A SHALLOW BAY. Doctoral dissertation, Texas A&M University. Available electronically from