The model equations for storm surge and tsunamis most commonly used are the shallow water equations with addition of appropriate source terms for bathymetry. Traditional approaches will need to resolve the mesh to discretize small-scale structure, which impacts the time-step size to be proportional to the size of cells. In this thesis, a novel approximate Riemann solver was developed in order to deal with the existence of barrier without restricting the time-step due to small cells. Because of the wave redistribution method and proper ghost cells setting, the novel Riemann solver maintained properties including mass and momentum conservation, the well-balancing properties and robustness at the wet-dry interface. The solver also preserves nonnegative water depth and prevents leakage. A modified h-box method is applied so the algorithm can overcome restrictions of small time-step sizes. The work has been done in the context of the GeoClaw platform with retaining the capabilities of GeoClaw solver. At the same time, the special developed Riemann solver extends the package to handle the sub-grid-scale effects of barriers. Incorporating the solver developed in this work into the GeoClaw framework has allowed to leverage GeoClaw’s ability to handle complex bathymetry and real applications.

Thesis (M.S.)--Oregon State University, 2009. / Printout. Includes bibliographical references (leaves 54-55). Also available on the World Wide Web.

Thesis (M. Sc.)--University of Hong Kong, 2007. / Title proper from title frame. Also available in printed format.

Thesis (M. Sc.)--University of Canterbury, 2008. / Typescript (photocopy). Includes bibliographical references (leaves 103-116). Also available via the World Wide Web.

Thesis (Ph. D.)--University of California, San Diego, 2000. / Vita. Includes bibliographical references.

Storm induced flooding presents a multifaceted threat to coastal communities across the world.With climate change and sea level rise this danger is expected to increase. As coastal communities become exposed to more frequent and more severe flooding, the need for protective measures will increase. To know how to optimally protect against coastal flooding requires an understanding of future flood risk, storms, and storm surge. These are challenging to estimate due to many sources of uncertainty. In this thesis I present a methodology to forecast this future flood risk. I combine multiple computational, physics and statistical models to accurately describe the fluid dynamics of flooding, the cyclones that drive surge, and how climate change will influence these different components in the future. These computational models must be fast so that they can be embedded into an optimization framework that makes many evaluations. To find an optimal protective measure I employ stochastic and derivative free optimization methods. A complete study is conducted on New York City and optimal protective strategies are found for minimizing the total cost from storm surge subject to different budget constraints.

published_or_final_version / abstract / Applied Geosciences / Master / Master of Science

When the effects of wind and air pressure combine with a high tide to give unusually high water levels this can lead to severe coastal flooding. This happened in England in early 1953 when 307 people died in the East Coast Flood. In Britain today such events, now called storm surges, are forecast daily using computer models from the National Oceanographic Centre in Liverpool, formerly the Liverpool Tidal Institute (TI). In 1919, when TI was established, such events were considered unpredictable. TI's researchers, Joseph Proudman (1888-1975), Arthur Doodson (1890-1968), Robert Henry Corkan (1906-1952) and Jack Rossiter (1919-1972), did much mathematical work to attempt to change this. In 1959 Rossiter published a set of statistical formulae to forecast storm surges on the East Coast and a national warning system was predicting such events using these formulae. At this point TI believed they had made surges at least as predictable as they could with their existing methods. This thesis provides a narrative of how this perceived rise in the predictability of surges happened, analysing how TI worked to achieve it between 1919 and 1959 by following two interwoven, contingent and contested threads: practices of calculation and patronage. A key aspect of this thesis is the attention I pay to material practices of calculation: the methods, technologies and management practices TI's researchers used in their mathematical work on storm surge forecasting. This is the first study by historians of oceanography or meteorology that pays this detailed level of attention to such practices in the construction of forecasting formulae. As well as using published accounts, I analyse statistical research in the making, through notes, calculations, graphs and tables produced by TI's researchers. They used particular practices of calculation to construct storm surges as calculable and predictable scientific objects of a specific kind. First they defined storm surges as the residuals derived from subtracting tidal predictions from observations. They then decided to use multiple regression, correlating their residuals with pressure gradients, to make surges predictable. By considering TI's practices of calculation the thesis adds to the literature on mathematical research as embodied and material, showing how particular practices were used to make a specific phenomenon predictable. I combine this attention to mathematical practice with analysis of why TI's researchers did this work. US historians have emphasised naval patronage of physical oceanography in this period but there is very little secondary literature for the British case. The thesis provides a British case study of patronage of physical oceanography, emphasising the influence on TI's work not only of naval patronage but also of local government, civil state and industrial patronage. Before TI's establishment Proudman argued that it should research storm surges to improve the Laplacian theory of tides. However, when the new Institute received patronage from the local shipping industry this changed and the work on forecasting surges was initially done as part of a project to improve the accuracy of tidal predictions, earning TI further patronage from the local shipping industry. After a flooding event in 1928 the reasons for the work and the patronage again shifted. Between then and 1959 TI did this work on commission from various patrons, including local government, civil state and military actors, which connected their patronage to national debates about state involvement in flood defence. To understand why TI's researchers worked on forecasting surges I analyse this complex mix of patrons and motivations. I argue that such complex patronage patterns could be fruitfully explored by other historians to further existing debates on the patronage of oceanography.

A topology-based approach has been used to measure the resilience of a highway network to climatic events. Civil infrastructure systems are inarguably critical to the everyday functions of society. Because such systems are regionally distributed, their components undergo a wide range of hazard intensities, often dependent on their relative locations. The ability of an infrastructure system to withstand, adapt to, and rapidly recover from extreme events is paramount to its ability to continuously serve users. The topological properties of a network can provide a good means to assess the resilience of the system which is adequate to comprehend the preparedness and functionality of an infrastructure system in the face of various hazards. Hurricanes and storm surges are especially relevant on the eastern coast of the US, where they can cause widespread damage and destruction. Furthermore, the effects of climate change are proven to increase the intensity of climatic events, worsening the consequences to infrastructure networks. The vulnerability of the transportation network of New York City, the most populous urban area in the U.S., was underlined in the aftermath of Hurricane Sandy, and for this purpose has been chosen as the test bed for this study. Reducing the highway system to a combination of nodes and links, the principles of graph theory are applied to quantify defining network properties. More specifically, by assessing and measuring the change in topological properties during extreme climatic events, the resilience of a transportation network can be succinctly evaluated.

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