Physical Sciences and Mathematics Commons^™

Assessing The Rates Of Post-Depositional Change Within 2004 Indian Ocean Sediments: Implications For Long-Term Records Of Paleotsunamis, Lillian Pearson

Master's Theses

Foraminifera are commonly used to examine patterns of tsunami inundation occurring over centennial to millennial timescales, but the impacts of post-depositional change on geologic reconstructions are unknown. In Sumatra, the taphonomic character (i.e., test surface condition) of a foraminifer can deteriorate over time, rendering them unidentifiable, and even dissolve them entirely. Here I investigate the rates of post-depositional change of foraminiferal assemblages found within the 2004 Indian Ocean Tsunami (IOT) deposit over a 15-year time interval in Aceh, Indonesia in a vegetated open coastal plain (Site 1: Pulot) and an unvegetated protected coastal cave (Site 2). I identified two zones …

Ensemble Data Fitting For Bathymetric Models Informed By Nominal Data, Samantha Zambo

Dissertations

Due to the difficulty and expense of collecting bathymetric data, modeling is the primary tool to produce detailed maps of the ocean floor. Current modeling practices typically utilize only one interpolator; the industry standard is splines-in-tension.

In this dissertation we introduce a new nominal-informed ensemble interpolator designed to improve modeling accuracy in regions of sparse data. The method is guided by a priori domain knowledge provided by artificially intelligent classifiers. We recast such geomorphological classifications, such as ‘seamount’ or ‘ridge’, as nominal data which we utilize as foundational shapes in an expanded ordinary least squares regression-based algorithm. To our knowledge …

Application Of Machine Learning Techniques To Forecast Harmful Algal Blooms In Gulf Of Mexico, Bala Tripura Sundari Yerrapothu

Master's Theses

The Harmful Algal Blooms (HABs) forecast is crucial for the mitigation of health hazards and to inform actions for the protection of ecosystems and fisheries in the Gulf of Mexico (GoM). For the sake of simplicity of our application we assume ocean color satellite imagery from the National Oceanic and Atmospheric Administration as a proxy for HABs.

In this study we use a deep neural network trained on the 2-Dimensional time series proxy data to provide a forecast of the HABs’ manifestations in the GoM.Our approach analyzes between both spatial and temporal features simultaneously. In addition, the network also helps …

Microplankton Dynamics In The River-Dominated Mississippi Bight, Adam D. Boyette

Dissertations

The Mississippi Bight (MSB) is a river-dominated continental margin influenced by multiple large river systems, including the Mississippi River, Alabama and Tombigbee rivers via Mobile Bay, and numerous smaller rivers, creeks, and bayous. This is part of a biologically-rich ecosystem that supports the second largest fishery industry by volume in the United States. Despite our understanding of the linkages between primary production with higher trophic levels, there remains limited studies quantifying these trophic interactions in this system. Microplankton (µm) community dynamics and trophic connectivity between primary producers and heterotrophic protists represent a critical nexus influencing overall biological productivity in this …

Assessing The Real-Time Lagrangian Predictability Of The Operational Navy Coastal Ocean Model In The Gulf Of Mexico, Lea Kristen Locke

Dissertations

This study quantitatively assesses the drift predictive skill of Fleet Numerical Meteorology and Oceanography Center’s (FNMOC’s) operational ocean models which are used to support a wide range of military and civilian applications. Overall, the findings of this work support the recommendation of spatial filtering for regional-scale ocean model velocity fields used in deep-water drift applications. In conjunction with filtering, the use of a pure particle drift algorithm is suggested for short-term forecasts and a drift algorithm including a sub-grid scale, random flight, parameterization for predictions requiring extended forecast predictions.

Drift prediction skill is quantified through metrics of in-cloud percentage, distance …

Small-Scale Resuspension And Redistribution Of Surface Sediments In The Northeast Gulf Of Mexico, Austin Harris

Master's Theses

Following the release of ~4.9 million barrels of oil into the Gulf of Mexico from the Macondo wellhead, a vast area of the seafloor contained recently deposited marine sediments contaminated by the oil spill. The initial deposition of these contaminated marine sediments was likely not the end of the journey for the particles. Downslope gravitational processes and events of increased current speed in the deep ocean setting can result in recently deposited sediments to resuspend and be moved laterally with the current flow, increasing the area effected by the oil spill. Erosion experiments performed in a closed-loop resuspension flume were …