Idealized bathymetries were subjected to idealized cyclones in order to measure the storm surge response to a range of bathymetry features, under various storm conditions. Ten bathymetries were considered, including eight shoals, one pit, and a featureless reference domain. Six storms (two different sizes/intensities and three different landfall directions) were used as meteorological forcing. The bathymetry features influenced local surge response during pre- and post-peak surge conditions. However, peak surge and surge at the coast were not meaningfully affected by the presence of the bathymetry features considered. The effect of three bathymetry feature parameters on surge response was analyzed (i.e. depth below mean sea level, cross-shore width, and distance from shore). Of these parameters, feature depth below mean sea level was the most influential on surge generation.

Hurricanes strike the coast along the Gulf of Mexico and eastern seaboard of the United States annually. With each hurricane that makes landfall there is potential for significant damage and destruction with the majority of coastal devastation occurring from storm surge. It is accepted that hurricane strength, classified byt the Saffir-Simpson scale, and storm surge height are directly proportional. However, this scale my prove to be a false representation of surge height, especially according to location of landfall. This study will discuss the correlation between category 2, and greater, hurricanes and corresponding storm surge heights between the Gulf Coast and Atlantic coast. Through this research it shows that there is a variation in storm surge height between regions, concluding that the Gulf Coast is prone to higher surge heights than the Atlantic for like-category storms.

This thesis presents a technique for storm surge forecasting. Storm surge is the water that is pushed toward the shore by the force of the winds swirling around the storm. This advancing surge combines with the normal tides to create the hurricane storm tide, which can increase the mean water level by almost 20 feet. Numerical modeling is an important tool used for storm surge forecast. Numerical model ADCIRC (Advanced Circulation model; Luettich et al, 1992) is used in this thesis for simulating hurricanes. A statistical technique, EST (Empirical Statistical Technique) is used to generate life cycle storm surge values from the simulated hurricanes. These two models have been applied to Freeport, TX. The thesis also compares the results with the model SLOSH (Sea, Lake, and Overland Surges from Hurricanes), which is currently used for evacuation and planning. The present approach of classifying hurricanes according to their maximum sustained winds is analyzed. This approach is not found to applicable in all the cases and more research needs to be done. An alternate approach is suggested for hurricane storm surge estimation.

A spatial-temporal model is developed for modelling the impacts of simulated coastal zone storm surge and flooding using a combined spatial mapping and system dynamics approach. By coupling geographic information systems (GIS) and system dynamics, the interconnecting components of the spatial-temporal model are used with limited historical data to evaluate storm damage. Overlapping cumulative effects layers in GIS (ArcMap) are used for describing the coastal community’s profile, and a system dynamics feedback model (STELLA) is developed to define the interconnecting component relationships of the community. The component-wise changes to the physical environment, community infrastructure, and socioeconomic resources from the storm surge and seal level rise are examined. These changes are used to assess the impacts of the community system as a whole. For the purpose of illustrating this model, the research is applied specifically to the case of Charlottetown, Prince Edward Island, Canada, a vulnerable coastal city subject to considerable impacts from pending sea level rise and more frequent severe storm surge attributed to the changing climate in the coastal zone.

A spatial-temporal model is developed for modelling the impacts of simulated coastal zone storm surge and flooding using a combined spatial mapping and system dynamics approach. By coupling geographic information systems (GIS) and system dynamics, the interconnecting components of the spatial-temporal model are used with limited historical data to evaluate storm damage. Overlapping cumulative effects layers in GIS (ArcMap) are used for describing the coastal community’s profile, and a system dynamics feedback model (STELLA) is developed to define the interconnecting component relationships of the community. The component-wise changes to the physical environment, community infrastructure, and socioeconomic resources from the storm surge and seal level rise are examined. These changes are used to assess the impacts of the community system as a whole. For the purpose of illustrating this model, the research is applied specifically to the case of Charlottetown, Prince Edward Island, Canada, a vulnerable coastal city subject to considerable impacts from pending sea level rise and more frequent severe storm surge attributed to the changing climate in the coastal zone.

This thesis presents a technique for storm surge forecasting. Storm surge is the water that is pushed toward the shore by the force of the winds swirling around the storm. This advancing surge combines with the normal tides to create the hurricane storm tide, which can increase the mean water level by almost 20 feet. Numerical modeling is an important tool used for storm surge forecast. Numerical model ADCIRC (Advanced Circulation model; Luettich et al, 1992) is used in this thesis for simulating hurricanes. A statistical technique, EST (Empirical Statistical Technique) is used to generate life cycle storm surge values from the simulated hurricanes. These two models have been applied to Freeport, TX. The thesis also compares the results with the model SLOSH (Sea, Lake, and Overland Surges from Hurricanes), which is currently used for evacuation and planning. The present approach of classifying hurricanes according to their maximum sustained winds is analyzed. This approach is not found to applicable in all the cases and more research needs to be done. An alternate approach is suggested for hurricane storm surge estimation.

A spatial-temporal model is developed for modelling the impacts of simulated coastal zone storm surge and flooding using a combined spatial mapping and system dynamics approach. By coupling geographic information systems (GIS) and system dynamics, the interconnecting components of the spatial-temporal model are used with limited historical data to evaluate storm damage. Overlapping cumulative effects layers in GIS (ArcMap) are used for describing the coastal community’s profile, and a system dynamics feedback model (STELLA) is developed to define the interconnecting component relationships of the community. The component-wise changes to the physical environment, community infrastructure, and socioeconomic resources from the storm surge and seal level rise are examined. These changes are used to assess the impacts of the community system as a whole. For the purpose of illustrating this model, the research is applied specifically to the case of Charlottetown, Prince Edward Island, Canada, a vulnerable coastal city subject to considerable impacts from pending sea level rise and more frequent severe storm surge attributed to the changing climate in the coastal zone.

Coastal storm surges from hurricanes are one of the most costly natural disasters in the United States (US). Current research arguably indicates a mean sea-level (MSL) increase due to global warming, as well as an increase in damages caused by hurricanes under climate change. The objectives of this research are: 1) to develop a framework that integrates Geographical Information Systems (GIS) with hurricane storm surge numerical models; 2) to quantify the uncertainty derived from coastal land cover spatial data on hurricane storm surge; and 3) to investigate the potential impacts of SLR changes on land cover to hurricane storm surge and coastal damages. Numerical analysis is an important tool for predicting and simulating storm surges for coastal structure design, planning and disaster mitigation. Here we proposed a framework to integrate Geographical Information Systems (GIS) with computational fluid dynamic (CFD) models used to simulate hurricane storm surge. The geodatamodel "Arc StormSurge" is designed to store geospatial information for hurricane storm surge modeling and GIS tools are designed to integrate the high performance computing (HPC) input and output files to GIS; pre-process geospatial data and post-process model results, thereby, streamlining the delineation of coastal flood maps. Georeferenced information of land cover is used to define the frictional drag at the sea bottom and to infer modifications to the momentum transmitted to the water column by the winds. We investigated uncertainties in the surge response arising from land cover for Texas central bays considering several land cover datasets. The uncertainties were quantified based on the mean maximum surge response and inundated area extent. Considering projected SLR, wetland composition and spatial distribution are also expected to change with coastal environmental conditions. Our results showed that wetland degradation by SLR increased the mean maximum surge for coastal bays. Direct damage to buildings and businesses was also significantly increased by the loss of wetlands due to SLR. Here, we demonstrated the importance of considering the effects of land cover and SLR to hurricane storm surge simulations for coastal structure design, floodplain delineation or coastal planning.

A spatial-temporal model is developed for modelling the impacts of simulated coastal zone storm surge and flooding using a combined spatial mapping and system dynamics approach. By coupling geographic information systems (GIS) and system dynamics, the interconnecting components of the spatial-temporal model are used with limited historical data to evaluate storm damage. Overlapping cumulative effects layers in GIS (ArcMap) are used for describing the coastal community’s profile, and a system dynamics feedback model (STELLA) is developed to define the interconnecting component relationships of the community. The component-wise changes to the physical environment, community infrastructure, and socioeconomic resources from the storm surge and seal level rise are examined. These changes are used to assess the impacts of the community system as a whole. For the purpose of illustrating this model, the research is applied specifically to the case of Charlottetown, Prince Edward Island, Canada, a vulnerable coastal city subject to considerable impacts from pending sea level rise and more frequent severe storm surge attributed to the changing climate in the coastal zone.

Urbanization in coastal areas of the United States is increasing as simultaneously the East and Gulf coasts of the United States face increasing threats from climate change from hurricanes and storm surge inundation. This study will evaluate urban growth using a cellular automata model to analyze the trends in urbanization between 1996 and 2019 and predict how it will continue until 2050. The study uses historical trends in land use and urbanization, as well as spatial and environmental data, to evaluate the likelihood of urban growth in two modeled scenarios: one that accounts for flood risk and one that does not. The study evaluates trends over the entire coastal buffer area, including the 150-kilometers adjacent to the East and Gulf coasts as well as targeted areas of New Orleans, Louisiana and Houston, Texas to determine growth at the scale of a metropolitan area. Both the scenarios have an overall prediction accuracy of 93% in determining the projected land use of a cell on the gridded map; however, the two models have different strengths. The scenario excluding storm surge impacts better predicts urban growth across the entire study area categorically, while the scenario accounting for the suitability of growth in areas at risk of storm surge inundation is more reliable in showing the specific areas urban growth occurred. The comparison of the strengths and weaknesses of the models will help determine if urbanization and population shifts are impacted by threats of storm surge and hurricanes in the study area. The outcome of the model analysis can be used to influence how communities burdened by climate change can strategically grow to limit the impacts of flooding on their residents and infrastructure. / Master of Science / The flood impacts of hurricanes regularly impact the coastline of the United States, however populations in the same coastal areas are continuing to grow. This study models how cities are growing along East and Gulf coasts and the factors influencing that growth. The concern with increasing urban areas in coastal areas is that these areas are also being affected by climate change, which can cause flooding and other dangerous conditions. These flood events are a risk to human lives and the built environment of the communities. This study uses a computer model to analyze how these cities are growing using historic data from 1996 to 2019 and how they will continue to grow through 2050. The model considers factors like the risk of flooding, as well as information about the land and environment in these areas. This study used this information to identify how cities are growing and determine if there is a need to better account for flooding risks and other problems caused by climate change as growth continues. The work looked at two different scenarios, one that accounts for flood risk and one that allows growth without concern for flood risk, to see which one more closely models historic growth. This study will help communities along the coast make smart decisions about how to grow and adapt to the challenges of climate change.