No description available.

Thesis (Ph.D.)--University of Delaware, 2006. / Principal faculty advisor: John A. Madsen, Dept. of Geological Studies. Includes bibliographical references.

Thesis (M.Oc.E)--Oregon State University, 2008. / Printout. Includes bibliographical references (leaves 83-86). Also available on the World Wide Web.

No description available.

A new method for automatically integrating the results of hydrodynamic models of currents in Texas bays with the National Oceanic and Atmospheric Administration’s (NOAA) in house oil spill trajectory model, the General NOAA Operational Modeling Environment (GNOME), is presented. Oil spill trajectories are predicted by inputting wind and water current forces on an initial spill in a dedicated spill trajectory model. These currents can be field measured, but in most real and meaningful cases, the current field is too spatially complex to measure with any accuracy. Instead, current fields are simulated by hydrodynamic models, whose results must then be coupled with a dedicated spill trajectory model. The newly developed automated approach based on Python scripting eliminates the present labor-intensive practice of manually coupling outputs and inputs of the separate models, which requires expert interpretation and modification of data formats and setup conditions for different models. The integrated system is demonstrated by coupling GNOME independently with TXBLEND – a 2D depth-averaged model which is currently used by the Texas Water Development Board, and SELFE – a newer 3D hydrodynamic model with turbulent wind mixing. A hypothetical spill in Galveston Bay is simulated under different conditions using both models, and a brief qualitative comparison of the results is used to raise questions that may be addressed in future work using the automated coupling system to determine the minimum modeling requirements for an advanced oil spill nowcast/forecast platform in Texas bays. / text

Thesis (Ph.D.)--University of Delaware, 2008. / Principal faculty advisors: Stephen Craig Cary and Kathryn J. Coyne, College of Marine & Earth Studies. Includes bibliographical references.

Thesis (M.A.G.)--Texas State University-San Marcos, 2004. / Vita. Appendices: leaves 269-302. Includes bibliographical references (leaves 303-318).

Thesis (M.A.G.)--Texas State University-San Marcos, 2004. / Vita. Appendices: leaves 269-302. Includes bibliographical references (leaves 303-318).

Thesis (M.C.E.)--University of Delaware, 2006. / Principal faculty advisors: Dominic M. Di Toro and James T. Kirby, Dept. of Civil & Environmental Engineering. Includes bibliographical references.

Numerical modeling of shallow microtidal semi-enclosed estuaries requires the effective simulation of physical processes with a wide range of temporal and spatial scales. In theory, application of sufficient grid resolution in both the horizontal and vertical should result in a reasonable simulation. However, in practice, this is not the case. Fully resolving the finest scales can be computationally prohibitive, and various algorithmic assumptions can break down at fine resolutions, leading to spurious oscillations in the solution. One method of simulating inherently cross-scale phenomena is to use multimodel approaches in which domain decomposition is used to divide the region into multiple subregions, each modeled by different submodels. These submodels are coupled to simulate the entire system efficiently. In general, the different models may involve different physics, they may be dimensionally heterogeneous or they may be both physically and dimensionally heterogeneous. A reduction in computational expense is obtained by using simpler physics and/or a reduced dimension model in the submodels. In this research, we look at the particular case of modeling shallow bays containing narrow, deep ship channels. In order to accurately model bay circulation, a model should capture the effect of these spatially localized navigational channels. Our research shows that modeling techniques currently used to simulate such systems using 2 dimensional or coarse resolution 3 dimensional estuary models misrepresent wind driven surface circulation in the shallow bay and tide driven volume fluxes through the channel. Fully resolving the geometry of the ship channel is impractical on all but large parallel computing clusters. We propose a more efficient method using the multimodel approach. This approach splits the estuary into a shallow bay region and a subsurface ship channel region. By separating the physical domain into two parts in this way, simpler models can be used that are targeted at the different physical processes and geometries dominant in each region. By using a low resolution 3D model (SELFE) in the shallow bay region, coupled through appropriate interface conditions with a 2D laterally averaged model, the effects of the ship channel on bay circulation are accurately represented at a fraction of the computational expense. In this research, this coupled model was developed and applied to an ideal shallow bay- ship channel system. The coupled model approach is found to be an effective strategy for modeling this type of system. / text