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Hurricanes are among the most catastrophic types of natural hazards, with the potential to cause serious losses in lives and property. While hurricanes rarely have a huge impact on the New York City area, they do have the potential to cause major damage to the city's transportation infrastructure. This research will deal with two main considerations--fragility curves and exceedance curves of vulnerable points in that infrastructure. The primary objective of this study is to provide a model for predicting future hurricane related storm surge patterns and for estimating possible levels of damage from future events in order to develop planning strategies to mitigate against possible damage. The first step is to describe the frequency of past storm surge events in New York City from 1920 to 2012 and determine a probability distribution for hurricane hazard about the maximum daily and yearly storm surges. The second step is to estimate potential probabilistic models by looking at the empirical data on storm surges in New York City. The last step is to concentrate on the reliability assessment for several infrastructures subjected to hurricane loading and storm surges. No significant studies have been conducted using the available empirical data on storm surge heights in New York City, despite the fact that since an observation station was installed in the Battery, New York in 1920, daily and yearly maximum water levels at that location have been documented by the National Oceanic and Atmospheric Administration (NOAA). Considering the available daily maximum sea water levels from 1920 to 2012 yields a total of 31,148 data points (2,394 days of maximum height data are unfortunately missing); 92 data points of maximum sea water levels are also available. This is the first study to utilize the nearly century's worth of empirical data obtained by the observation station at the Battery. Extensive goodness of fit testing (including the use of various probability papers) is performed on the empirical daily maximum sea water level data. It is concluded that the daily maximum sea water levels at the Battery from 1920 to 2012 follow closely a logistic distribution, with a mean value of 8.10 feet and a coefficient of variation (COV) of 9.63%. The methodology of analyzing the yearly maximum sea water levels is quite similar to that used for the daily sea water levels (and the analysis is performed independently). It is found that the yearly maximum sea water levels at the Battery from 1920 to 2012 follow closely a generalized extreme value (GEV) distribution with a mean value of 10.72 feet and a COV of 10.07%. Then, applying exact and asymptotic Extreme Value Theory, the parent GEV distribution is used to determine the probability distributions for maximum sea water levels over a range of different multi-year periods including 1, 10, 50, 100, 200, and 500 years. Finally, the total volume of flood-vulnerable infrastructure is generated and flood damage probabilities when related to the established probability distributions for sea water levels are considered. The flood vulnerabilities of different parts of the built infrastructure in New York City are studied; specifically, the subway system and the tunnel system. The concept of fragility curves is used to express these vulnerabilities. Conclusions and recommendations are provided for estimating losses probabilistically over different periods, retrofitting and strengthening the infrastructure to reduce future potential losses, and determining repair priorities. This is very useful for cost-benefit analysis.

Hurricane Katrina hit the Gulf Coast on August 29th, 2005. It is considered to be one of the costliest and devastating disasters in the history of the United States. The storm flooded 70% of New Orleans resulting in more than 1,500 people losing their lives and the displacement of an entire urban population. Reconstruction over the past ten years has revitalized much of New Orleans, demonstrating a great resilience and determination of its people. Nonetheless, New Orleans is also experiencing the long-term effects of Hurricane Katrina where victims of domestic violence and the institutions that serve them have been forever changed. This dissertation examines perceptions of domestic violence and help-seeking behaviors among women in post-Hurricane Katrina New Orleans from 2005 to 2015. Findings show that many women face striking inequalities demonstrated in higher rates of poverty, lack of affordable housing, and one of the highest wage gaps in the United States. Patriarchal attitudes seen in legal institutions, the police force, and political systems contribute to the perception of a gender bias against women. This qualitative research uses a case study methodology and employs ethnographic methods of observation, including 31 in-depth interviews that capture the complexity of domestic violence and identify the social and economic dynamics that create barriers to help-seeking in New Orleans. The data contends that women who have increased access to informal and formal networks are able to enact behaviors that will allow them to seek help and extricate themselves from abusive relationships. These findings demonstrate that inequalities in post-disaster reconstruction have created barriers to help-seeking among victims of domestic violence. These barriers include the destruction of social capital, institutional failures, and limited economic resources. Likewise, findings reveal that attitudes and behaviors regarding domestic violence help-seeking are dependent on social and economic well-being. This highlights the need for more research and hard data on the incidence of domestic violence in New Orleans to learn the exact scope of the problem and how to overcome the social and economic barriers that perpetuate the cycle of domestic violence. / 1 / Kelley Virginia Ponder

Hurricane Sandy made landfall in Brigantine, New Jersey on October 29th, 2012. The storm impacted the coastal regions of New Jersey and New York, especially the heavily populated area of New York City. This research, which analyzes secondary data obtained from a telephone survey, investigates the public response of residents before, during and after Hurricane Sandy. The survey consisted of questions regarding what the residents expected concerning the threat of Hurricane Sandy, whether it matched what they experienced, where they got their information and how they made their decision to evacuate or not. The results from the survey were statistically analyzed in order to answer important research questions about public perception of Sandy's impacts. A Vulnerability Assessment of New York City, where some of Sandy's impacts were felt the most, was completed in order to understand why this area was so vulnerable. The concern level of various hurricane related hazards was analyzed and correlated to demographic variables to determine a relationship among the variables. A qualitative analysis was performed on the survey questions "Why did you evacuate?" and "Why did you not evacuate?" in order to determine themes in relation to people's reasons for evacuating or not evacuating. Finally, differences in how the public perceived Hurricane Sandy before and after the storm were analyzed and may be used for improving communication of the forecast to the public. Interdisciplinary research in this area is needed in order to better understand the public's need for appropriate warnings to ensure safety. Results show that residents were most concerned about wind damage and that they mainly used their television to obtain their information about the storm. Also, the most common reasons respondents reported for evacuating were because of the threat of possible impacts (storm surge, flooding, wind, rain and waves), the forecast called for bad conditions, or being told, recommended or convinced to leave. The main reasons reported by respondents for not evacuating are thinking that the impacts would not be bad in their area, feeling prepared or safe and thinking they could handle the impacts. This research can be used in the future for improving hurricane warning communication to the public.

This thesis seeks to identify locations in which errors in numerical model initial conditions may compromise skill in tropical cyclone (TC) track forecasts. Two major TCs that made landfall in 2008 are analyzed: Hurricane Ike and Typhoon Sinlaku. In order to examine the sensitivity of the TC to selected synoptic features, a vorticity perturbation technique is developed. Within a chosen radius and atmospheric depth, the vorticity is amplified or decreased, followed by a re-balancing of the fields. The following questions are proposed: (1) How does the TC track vary with respect to initial perturbations of differing amplitude, spatial scale and distance to the storm? (2) How does the evolving perturbation act to modify the synoptic environment surrounding the TC, and thereby the track? (3) Is it best to follow an objective technique to determine the sensitive areas, or is it better to use a subjective method based on fundamental synoptic reasoning? Utilizing the Weather Research and Forecasting (WRF) model, the ?control? simulation for each TC is found to replicate forecast errors evident in the operational global models. For Sinlaku, this includes a premature recurvature in the forecast. For Ike, this comprises a landfall too far south along the Texas coast due to no recurvature being forecast. The size, magnitude and location of vorticity perturbations to the control analysis are chosen subjectively. For Sinlaku, these locations include a large mid-latitude shortwave trough around 3000 km to the north-northwest, a smaller upper-level shortwave immediately to the north, a low-level monsoon trough to the west-southwest, a weak tropical storm to the northeast, and a local perturbation in the immediate environment. It is found that WRF forecasts of Sinlaku exhibit high sensitivity, with large modifications to its track arising from the perturbation of each selected targets in the synoptic environment. The greatest improvement in the track forecast occurs by weakening the vorticity associated with each of two shortwaves to the north of Sinlaku, suggesting that either or both of the shortwaves may have been initialized too strongly in the model analysis, thereby contributing to an erroneous recurvature. For Ike, the perturbation locations include a large mid-latitude shortwave trough 2500 km to its north, an upper-level cutoff low to the east-northeast, a low-level shortwave trough to the northwest, a tropical storm in the East Pacific, and a local perturbation in the immediate environment. In contrast to Sinlaku, the perturbation of synoptic targets around Ike produces less sensitivity, likely due to the fact that Ike is not in a position of imminent recurvature. The only perturbation that leads to an accurate 4-day forecast of recurvature and landfall in North Texas is the strengthening of the large mid-latitude shortwave trough, suggesting that the shortwave may have been initialized too weakly in the operational models. Finally, a comparison of targets selected objectively by the Ensemble Transform Kalman Filter (ETKF) versus the above subjectively-chosen targets suggests that while the ETKF effectively indicates similar target regions to those selected subjectively, it may be less effective in ranking the relative sensitivities of those targets. Overall, it is found that the TC track is more sensitive to perturbations of larger amplitude and spatial scale, and less so to the distance between the perturbation and the TC, and sensitivity is confined to specific regions of the flow. The perturbation methodology employed here may be used to offer suggestions of locations in which extra high-density satellite data may be assimilated.

Bridges are the most critical components of the transportation network. The functionality of bridges is important for hurricane aftermath recovery and emergency activities. However, past hurricane events revealed the potential susceptibility of these bridges under storm induced wave and surge loads. Coastal bridges traditionally were not designed to sustain hurricane induced wave and surge loads; and furthermore, no reliability assessment tool exists for bridges exposed to this hazard. However, such a tool is imperative for decision makers to evaluate the risk posed to the existing bridge inventory, and to decide on the retrofit measures and mitigation strategies. This dissertation offers a first attempt to quantify the structural vulnerability of bridges under coastal storms, offering a probabilistic framework, input tools, and application illustrations. To accomplish this goal, first an unbiased wave load model is developed based on the existing wave load models in the literature. The biased is removed from the load models through statistical analysis of the experimental test data. The developed wave load model is used to evaluate the response of coastal bridges employing single-physics domain Dynamic numerical models. Additionally, a high fidelity fluid-structure interaction model is developed to take into account the significant intricacies, such as turbulence, wave diffraction, and air entrapment, as well as material and geometric nonlinearities in structure. This numerical model provides insight on the influential parameters that affect the response of coastal bridges. Moreover, a Monte Carlo based Static Model methodology is developed to enable fast evaluation of the bridge deck unseating mode of failure. This methodology can be used for fast screening of vulnerable structures under hurricane induced wave and surge loads in a large bridge inventory. New statistical learning tools are used to develop fragility surfaces for coastal bridges vulnerable to storms. The performance of each of these tools is evaluated and compared. The statistical learning approaches are used to enable reliability assessment using the more rigorous finite element models such as the Dynamic and FSI Models which is important for improved confidence and retrofit assessment. Additionally, a new systematic method to evaluate the limit state capacity functions based on the post-event global performance of the bridge structure is developed. The application of the developed reliability models is illustrated by utilizing them for Houston/Galveston Bay area bridge inventory. The case study of Houston/Galveston Bay area reveals that more than 30% of bridges have a high probability of failure during an extreme hurricane scenario event. Two vulnerable bridge structures from the case study are selected to investigate the effect of different potential retrofit measures. Recommendations are made for the most appropriate retrofit measures that can prevent the deck unseating without significantly increasing the structural demands on other components.

Open coastlines are dynamic environments which experience seasonal and long-term physical changes. Sandy beaches line much of this coastline. As part of the requirements for Ph.D., I conducted a study examining intertidal macrofaunal and sedimentological features along the upper Texas coastal from 2007-2009. Four sites near Sabine Pass, High Island, Jamaica Beach, and Surfside Beach were selected. Beach transects were established at each site with six intertidal stations identified for collecting macrofaunal sediment core samples. Although sandy beaches are low in species diversity, the taxa found survive under dynamic and harsh conditions. In disturbance dominated environments, sandy beach fauna tended to be influenced by physical factors, instead of biologically controlled ones. The taxa found in this study include primary and secondary successional organisms which are adapted to handle disturbances. 98% of the benthic specimens identified belonged to six taxa with 92% from two taxa, Scolelepis squamata (38%) and Haustoriidae (54%). Macrofaunal zonation varied between sites because of beach geomorphology. On September 13, 2008, Hurricane Ike made landfall on the upper Texas coast causing extensive damage and erosion. Roughly 0.5 m of vertical height was lost at each beach post-storm. Total macrofaunal abundance declined by 87% from pre-storm counts. During the recovery the dominant two taxa, Haustoriidae and Scolelepis squamata, made up 82.78% of the total benthic specimens identified with haustoriids making up 68% of the total benthic taxa. The beach community remained dominated by four of the previously identified, six most common and abundant taxa. Recovery of sandy beaches often was hindered by increased vehicular traffic, sand removal and cleaning. Beach ecosystems have shown a high natural ecological resilience, but do not preclude the possibilities of habitat extinction and/or catastrophic community regime shift. Beaches are highly susceptible to human exploitation and global climate change, such as sea level rise. Knowledge of beach macrofaunal diversity along the Texas coast, such as haustoriids, could be used to estimate beach health and better evaluate the upward effects of natural disturbance, pollution and human uses on an integral part of the coastal ecosystem.

The barrier islands of the gulf coast of the U.S. have been shaped and changed by hurricanes for centuries. These storms can alter the vegetation of the barrier islands by redistributing sediments, scouring off vegetation, physical damage to the plants, and by salt stress following the storm. Hurricanes also alter the mammal communities of the barrier islands through direct mortality and by altering vegetative communities. It is important to understand how the vegetation of barrier islands recovers after major hurricanes because the vegetation provides the structure that maintains and builds these islands. Following the landfall of Hurricane Katrina in August of 2005, I studied the changes in the herbaceous ground cover and the density of woody plants in Gulf Islands National Seashore in Mississippi from the winter of 2005 to the summer of 2007. Growth from existing plants and seed banks quickly revegetated the islands after the storm. The amount of live ground cover increased and bare ground decreased on each island and in every vegetation type. Most woody plant species also showed a net increase in density, with the exception of pine (Pinus elliottii) and Florida rosemary (Ceratiola ericoides). The regeneration of woody species and the uniform increase in the live ground cover seemed to indicate that the vegetation of the islands was not irreversibly impacted. I also studied the changes in the composition of mammal populations in Gulf Islands National Seashore from the winter of 2005 to the summer of 2007. Prior to the storm 11 terrestrial mammal species were recorded in studies of the barrier islands. In the 2 years following Hurricane Katrina, I recorded only 1 of the 7 species on Cat Island, 5 of the 9 species on Horn Island and 2 species each on East Ship, West Ship, and Petit Bois Islands (which previously had 4, 4, and 2 each). Populations of mammals that used multiple vegetation types (raccoons [Procyon lotor], nutria [Myocastor coypus], and eastern cottontail [Sylvilagus floridanus]) seemed to show more tolerance to hurricane disturbance than more specialized species (black rat [Rattus rattus], marsh rice rat [Oryzomys palustris]). I also recorded at least one colonization event by river otter (Lutra canadensis), a species not recently recorded on the islands. This research serves as a baseline for future comparison following similar storms.

Thesis (Ph. D.)--University of Florida, 2003. / Title from title page of source document. Includes vita. Includes bibliographical references.

A project is an organized endeavor aimed at accomplishing a specific nonroutine or low-volume task (Shtub, Barb, & Globerson, 2005). Natural hazards particularly hurricanes and flooding do not exactly match this definition, but the recovery from them does. Recovery is not only about restoration of structures, systems and services – although they are critical. A successful recovery is also about the individuals and families being able to rebound from their losses, and sustain their physical, social and economic well-being (Department of Homeland Security, 2010). To be able to do this requires a comprehensive disaster recovery plan comprised of consistent action to be taken before, during and after a disaster. Flooding and wind related damages from hurricanes and tropical storms create the most widespread natural hazard disasters resulting in billions of dollars in property losses each year. Southeast Texas is vulnerable to flooding because of its proximity to the Gulf of Mexico and its flat terrain. 2004, 2005, and especially the 2008 hurricane season have highlighted the need for additional guidance, structure and support specifically oriented to long-term disaster recovery. The 2008 hurricane season was particularly active for Texas with a tropical storm and three named hurricanes. Hurricane Ike was the largest to hit the Texas coast in history and the third most destructive in the nation’s history. An estimated total damage of $29 billion for the 2008 hurricane season devastated Texas (Office of the Governor of the State of Texas, 2008). Luckily, the recovery efforts for Hurricane Ike have been marked by positive outcomes when compared to previous responses to events, but more work could have been done in the pre-disaster planning of an event. This thesis will outline a process that will look at ways to mitigate the hazard by planning long-term to lessen the recovery time and lead to a more sustainable community by hardening infrastructure and strengthening residential building codes in anticipation of future disasters. / text