Tsunamis are gravity water waves that are generated by impulsive disturbances such as submarine earthquakes, landslides, volcanic eruptions, underwater explosions or asteroid impacts. Submarine earthquakes are the primary tsunami source, but landslides may generate tsunamis exceeding tectonic tsunamis locally, in both wave and runup heights. The field data on landslide tsunami events are limited, in particular regarding submarine landslide dynamics and wave generation. Tsunamis generated by three-dimensional deformable granular landslides are physically modeled in the NEES (Network of Earthquake Engineering Simulation) 3D tsunami wave basin (TWB) at Oregon State University in Corvallis, Oregon. A novel pneumatic landslide tsunami generator is deployed to simulate natural landslide motion on a hill slope. The instrumentation consists of various underwater, above water and particle image velocimetry (PIV) cameras, numerous wave and runup gauges and a multi-transducer acoustic array (MTA). The subaerial landslide shape and kinematics on the hill slope and the surface elevation of the offshore propagating tsunami wave and runup on the hill slope are measured. The evolution of the landslide front velocity, maximum landslide thickness and width are obtained along the hill slope. The landslide surface velocity distribution is obtained from the PIV analysis of the subaerial landslide motion. The shape and the size of the submarine landslide deposit are measured with the MTA. Predictive equations are obtained for the tsunami wave amplitude, wave period and wavelength in terms of the non-dimensional landslide parameters. The generated 3D tsunami waves propagate away from the landslide source as radial wave fronts. The amplitudes of the leading tsunami waves decay away from the landslide source in radial and angular direction. The wave celerity of the leading tsunami wave may be approximated by the solitary wave speed while the trailing waves are slower due to the dispersion effects. The energy conversion rate between the landslide and the generated wave is estimated. The observed waves are weakly non-linear in nature and span from shallow water to deep water depth regime. The unique experimental data serves the validation and advancement of numerical models of tsunamis generated by landslides. The obtained predictive equations facilitate initial rapid tsunami hazard assessment and mitigation.

This report focuses on using the Papathoma Tsunami Vulnerability Assessment Model (PTVA) to demonstrate the vulnerability of Cayucos to a 500-year tsunami, and using the results to inform specific planning recommendations. By modeling inundation with GIS and analyzing building attributes via the PTVA model, this study has gone beyond any previous vulnerability assessments of Cayucos. Findings include: delineation of the most vulnerable areas, estimates of numbers of lost civic buildings, commercial buildings and houses, as well as estimates of people displaced from tsunami damaged homes. The report goes on to discuss what mitigation measures are in place and what further specific steps could be taken to ensure the long term sustainability of the town and help reduce future tsunami losses. Cayucos is a small coastal town in San Luis Obispo County, California; popular with tourists and locals for its beach, pier, and downtown. Intense coastal development and low lying topography makes Cayucos among the most tsunami vulnerable communities in the county. Many civic and economically important buildings, as well as homes, are within the 500-year tsunami inundation area. In the absence of fully developed, and accessible assessment tools like FEMA’s HAZUS tsunami program; local planners have had only basic information to assess the community’s tsunami vulnerability. The Papathoma Tsunami Vulnerability Assessment Model (PTVA) is a method that uses available tsunami runup estimations and field data collection to produce a detailed assessment of individual building survivability and overall community vulnerability.

O presente trabalho tem como objetivo compreender os processos que conduzem a estabilidade e a evolução morfológica do canal do rio Itaguaré em Bertioga - SP em uma escala de tempo histórica. Para isso, foram realizados os seguintes itens: a caracterização do clima de ondas, caracterização sedimentar, interpretação de fotografias aéreas, mapeamento das feições e delimitação das áreas de perigo relacionada à existência do canal. A análise da caracterização do clima de ondas foi realizada no software CAROL com uma série temporal de 1948 a 2010. As amostras de sedimentos foram coletas e processadas em laboratório por peneiramento e analisadas estatisticamente no software LBSE. A evolução histórica da desembocadura envolveu a escolha de fotografias aéreas de diferentes datas, as quais foram georreferenciadas e extraídas as linhas de costa, feições geomorfológicas e parâmetros específicos para a determinação da área de perigo relacionada ao canal. A caracterização da Barra de Itaguaré indica que a praia é composta por areias fina e muito fina, com ondas de maior incidência de SSE, SE e S. Para a análise da variação da linha de costa adjacente ao canal foi visto que no setor 1 teve progradação máxima de aproximadamente 80m e o setor 2 uma retração máxima de 53m. O canal foi classificado como de baixa energia de migração possuindo uma área de perigo estimada em 1.830m. A desembocadura de Itaguaré durante o período observado é estável quanto à posição na linha de costa e instável geometricamente quanto a sua morfologia, durante o período observado. / The present study has the objective to understand the morphological evolution processes that lead the inlet of Itaguaré, in Bertioga - SP, to stability. Thus, we conducted the following items: a characterization of the wave climate, sediment characterization, aerial photo interpretation, mapping features and delimitation the related inlets hazards areas. The analysis of the wave climate characterization was done in software CAROL with a time series from 1948 to 2010. Sediments samples were collected in field and processed in a laboratory by sieving. These samples were statistically analyzed with the software LBSE. For the inlet historical evolution used aerial photographs of different dates, which were georeferenced and used to extract coastlines, geomorphologic features, and specific parameters for determining inlets hazardous areas. The main results obtained for Itaguaré\'s Bar characterization was that the beach is composed of fine and very fine sand, with waves with a higher incidence of SSE, SE and S. Analysis of coastline variability adjacent to the inlet showed that the sector 1 had maximum progradation of nearly 80m and the sector 2 had a maximum retraction of 53m.The inlet was classified as low-energy migration and has a hazard area of 1830m. It was observed that the Itaguaré inlet is stable with respect to the position at the coastline and geometrically unstable with respect to its morphology.

While environmental justice (EJ) research in the U.S. has traditionally focused on inequities in the distribution of technological hazards, the disproportionate impacts of Hurricane Katrina on racial minorities and socioeconomically disadvantaged households have prompted researchers to investigate the EJ implications of natural hazards such as flooding. Recent EJ research has also emphasized the need to examine social inequities in access to environmental amenities. Unlike technological hazards such as air pollution and toxic waste sites, areas exposed to natural hazards such as hurricanes and floods have indivisible amenities associated with them. Coastal property owners are exposed to flood hazards, but also enjoy water views and unhampered access to oceans and the unique recreational opportunities that beaches offer. Conversely, dense urban development and associated impervious surfaces increase likelihood of floods in inland areas which may lack the amenities of proximity to open water. This dissertation contributes to the emerging literature on EJ and social vulnerability to natural hazards by analyzing racial, ethnic, and socioeconomic inequities in the distribution of flood risk exposure in the Miami Metropolitan Statistical Area (MSA), Florida--one of the most hurricane-prone areas in the world and one of the most ethnically diverse MSAs in the U.S. The case study evaluates the EJ implications of residential exposure to coastal flood risk, inland flood risk, and no flood risk, in conjunction with coastal water related amenities, using geographic information science (GIS)-based techniques and logistic regression modeling to estimate flood risk exposure. Geospatial data from the Federal Emergency Management Agency (FEMA) are utilized to delineate coastal and inland 100-year flood hazard zones. Socio-demographic variables previously utilized in EJ research are obtained from tract level data published in the 2010 census and 2007-2011 American Community Survey five-year estimates. Principal components analysis is employed to condense several socio-demographic attributes into two neighborhood deprivation indices that represent economic insecurity and instability, respectively. Indivisible coastal water related amenities are represented by control variables of percent seasonal homes and proximity to public beach access sites. Results indicate that racial/ethnic minorities and those with greater social vulnerability based on the neighborhood deprivation indices are more likely to reside in inland flood zones and areas outside 100-year flood zones, while residents in coastal flood zones are disproportionately non-Hispanic White. Moreover, residents exposed to coastal flood risk tend to live in areas with ample coastal water related amenities, while racial/ethnic minorities and individuals with higher neighborhood deprivation who are exposed to inland flood risk or no flood risk reside in areas without coastal water related amenities. This dissertation elucidates the importance of EJ research on privilege and access to environmental amenities in conjunction with environmental hazards because areas exposed to natural hazards are likely to offer indivisible benefits. Estimating people and places exposed to hazards for EJ research becomes difficult when the boundaries of census areal units containing socio-demographic data do not match the boundaries of hazard exposure areas. This challenge is addressed with an application of dasymetric spatial interpolation using GIS-based techniques to disaggregate census tracts to inhabited parcels. Several spatial interpolation methods are assessed for relative accuracy in estimating population densities for the Miami MSA, and the output units from the most accurate method are employed in EJ regression analyses. The dasymetric mapping efforts utilized herein contribute to research on the modifiable areal unit problem (MAUP) and its effects on statistical analyses. Since the dasymetric mapping technique used for EJ analyses disaggregates census tracts to the inhabited parcel level, the results of the associated analyses for flood hazards exposure and access to coastal water related amenities should be more reliable than those based on tracts. The enhanced accuracy associated with inhabited parcels is a result of using a more precise geospatial depiction of residential populations, which leads to a more accurate portrayal of disproportionate exposure to flood hazards. Consequently, this dissertation contributes methodologically to GIS-based techniques of dasymetric spatial interpolation and empirically to EJ analysis of flood hazards with indivisible coastal water related amenities.

This dissertation combines seemingly different studies, which work together to describe the physical characteristics of rip current development and associated social implications at several locations. These fast-moving, concentrated flows of water travel offshore and can be found on any beach with sufficient wave action. Any event of increased wave steepness will erode a large quantity of sediment from the beach. The material deposited offshore eventually makes its way back; during this process, ocean water becomes trapped behind a shore-attached bar resulting in a ridge-and-runnel. These formations are seen at East Hampton, where rip-like currents form as concentrated water drains from the runnel through a breach in the ridge. Camera images from 2010-2016 captured ridge-and-runnel formations and the ensuing currents. These newly described rips behave similarly to bar-gaps; however, they are not directly related to wave action. Coastal scientists consider rip currents to be the number one hazard at most beaches. In Palm Beach County, two traditional rip types were studied: bar-gap and structurally-controlled. Lifeguard incident reports from 2011-2016 were used to correlate wind speeds and wave heights to rip related rescues at three beaches. This research was undertaken in an effort to determine under what conditions most beachgoers become caught in this hazard. Rip currents were seen to be the most dangerous to bathers on days with moderate wind and wave activity. The same beach states that lead to the strongest rips also tend to keep beachgoers from entering the ocean. A social survey at Miami Beach, from 2011 to 2012, quantified beachgoer’s rip knowledge and their recognition of hazards. A significant portion of the respondents showed insufficient knowledge, which indicated they are at-risk of being caught or drowning in a rip current. Frequent exposure to the beach, maturation, and residency were identified as the main contributors to one’s literacy whereas education was the only variable that influenced a beachgoer’s visual recognition of hazard. The information gathered by these surveys can aid in creating better rip current awareness campaigns targeted to demographics that were determined as the most at-risk. An understanding of the physical and social science of rip currents can mitigate the impact of these beach hazards.

abstract: Drawing from the fields of coastal geography, political ecology, and institutions, this dissertation uses Cape Cod, MA, as a case study, to investigate how chronic and acute climate-related coastal hazards, socio-economic characteristics, and governance and decision-making interact to produce more resilient or at-risk coastal communities. GIS was used to model the impacts of sea level rise (SLR) and hurricane storm surge scenarios on natural and built infrastructure. Social, gentrification, and tourism indices were used to identify communities differentially vulnerable to coastal hazards. Semi-structured interviews with planners and decision-makers were analyzed to examine hazard mitigation planning. The results of these assessments demonstrate there is considerable variation in coastal hazard impacts across Cape Cod towns. First, biophysical vulnerability is highly variable with the Outer Cape (e.g., Provincetown) at risk for being temporarily and/or permanently isolated from the rest of the county. In most towns, a Category 1 accounts for the majority of inundation with impacts that will be intensified by SLR. Second, gentrification in coastal communities can create new social vulnerabilities by changing economic bases and disrupting communities’ social networks making it harder to cope. Moreover, higher economic dependence on tourism can amplify towns’ vulnerability with reduced capacities to recover. Lastly, low political will is an important barrier to effective coastal hazard mitigation planning and implementation particularly given the power and independence of town government on Cape Cod. Despite this independence, collaboration will be essential for addressing the trans-boundary effects of coastal hazards and provide an opportunity for communities to leverage their limited resources for long-term hazard mitigation planning. This research contributes to the political ecology of hazards and vulnerability research by drawing from the field of institutions, by examining how decision-making processes shape vulnerabilities and capacities to plan and implement mitigation strategies. While results from this research are specific to Cape Cod, it demonstrates a broader applicability of the “Hazards, Vulnerabilities, and Governance” framework for assessing other hazards (e.g., floods, fires, etc.). Since there is no “one-size-fits-all” approach to mitigating coastal hazards, examining vulnerabilities and decision-making at local scales is necessary to make resiliency and mitigation efforts specific to communities’ needs. / Dissertation/Thesis / Doctoral Dissertation Environmental Social Science 2016

O presente trabalho tem como objetivo compreender os processos que conduzem a estabilidade e a evolução morfológica do canal do rio Itaguaré em Bertioga - SP em uma escala de tempo histórica. Para isso, foram realizados os seguintes itens: a caracterização do clima de ondas, caracterização sedimentar, interpretação de fotografias aéreas, mapeamento das feições e delimitação das áreas de perigo relacionada à existência do canal. A análise da caracterização do clima de ondas foi realizada no software CAROL com uma série temporal de 1948 a 2010. As amostras de sedimentos foram coletas e processadas em laboratório por peneiramento e analisadas estatisticamente no software LBSE. A evolução histórica da desembocadura envolveu a escolha de fotografias aéreas de diferentes datas, as quais foram georreferenciadas e extraídas as linhas de costa, feições geomorfológicas e parâmetros específicos para a determinação da área de perigo relacionada ao canal. A caracterização da Barra de Itaguaré indica que a praia é composta por areias fina e muito fina, com ondas de maior incidência de SSE, SE e S. Para a análise da variação da linha de costa adjacente ao canal foi visto que no setor 1 teve progradação máxima de aproximadamente 80m e o setor 2 uma retração máxima de 53m. O canal foi classificado como de baixa energia de migração possuindo uma área de perigo estimada em 1.830m. A desembocadura de Itaguaré durante o período observado é estável quanto à posição na linha de costa e instável geometricamente quanto a sua morfologia, durante o período observado. / The present study has the objective to understand the morphological evolution processes that lead the inlet of Itaguaré, in Bertioga - SP, to stability. Thus, we conducted the following items: a characterization of the wave climate, sediment characterization, aerial photo interpretation, mapping features and delimitation the related inlets hazards areas. The analysis of the wave climate characterization was done in software CAROL with a time series from 1948 to 2010. Sediments samples were collected in field and processed in a laboratory by sieving. These samples were statistically analyzed with the software LBSE. For the inlet historical evolution used aerial photographs of different dates, which were georeferenced and used to extract coastlines, geomorphologic features, and specific parameters for determining inlets hazardous areas. The main results obtained for Itaguaré\'s Bar characterization was that the beach is composed of fine and very fine sand, with waves with a higher incidence of SSE, SE and S. Analysis of coastline variability adjacent to the inlet showed that the sector 1 had maximum progradation of nearly 80m and the sector 2 had a maximum retraction of 53m.The inlet was classified as low-energy migration and has a hazard area of 1830m. It was observed that the Itaguaré inlet is stable with respect to the position at the coastline and geometrically unstable with respect to its morphology.

京都大学 / 0048 / 新制・課程博士 / 博士(地球環境学) / 甲第19875号 / 地環博第149号 / 新制||地環||30(附属図書館) / 32911 / 京都大学大学院地球環境学舎地球環境学専攻 / (主査)教授 藤井 滋穂, 教授 岡﨑 健二, 准教授 西前 出 / 学位規則第4条第1項該当 / Doctor of Global Environmental Studies / Kyoto University / DFAM

L'étude et la gestion des risques littoraux sont plébiscitées par notre société au vu des enjeux économiques et écologiques qui y sont impliqués. Ces risques sont généralement réponse à des conditions environnementales extrêmes. L'étude de ces phénomènes physiques repose sur la compréhension de ces conditions rarement (voire nullement) observées.Dans un milieu littoral, la principale source d'énergie physique est véhiculée par les vagues. Cette énergie est responsable des risques littoraux comme l'érosion et la submersion qui évoluent à des échelles de temps différentes (événementielle ou long-terme). Le travail réalisé, situé à l'interface de l'analyse statistique, de la géophysique et de l'informatique, vise à apporter des méthodologies et outils aux décideurs en charge de la gestion de tels risques.En pratique, nous nous intéressons à mettre en place des méthodes qui prennent en compte non seulement un site ponctuel mais traitent les problématiques de façon spatiale. Ce besoin provient de la nature même des phénomènes environnementaux qui sont spatiaux, tels les champs de vagues.L'étude des réalisations extrêmes de ces processus repose sur la disponibilité d'un jeu de données représentatif à la fois dans l'espace et dans le temps, permettant de projeter l'information au-delà de ce qui a déjà été observé. Dans le cas particulier des champs de vagues, nous avons recours à la simulation numérique sur calculateur haute performance (HPC) pour réaliser un tel jeu de données. Le résultat de ce premier travail offre de nombreuses possibilités d'applications.En particulier, nous proposons à partir de ce jeu de données deux méthodologies statistiques qui ont pour but respectif de répondre aux problématiques de risques littoraux long-termes (érosion) et à celles relatives aux risques événementiels (submersion). La première s'appuie sur l'application de modèles stochastiques dit max-stables, particulièrement adapté à l'étude des événements extrêmes. En plus de l'information marginale, ces modèles permettent de prendre en compte la structure de dépendance spatiale des valeurs extrêmes. Nos résultats montrent l'intérêt de cette méthode au devant de la négligence de la dépendance spatiale de ces phénomènes pour le calcul d'indices de risque.La seconde approche est une méthode semi-paramétrique dont le but est de simuler des champs spatio-temporels d'états-de-mer extrêmes. Ces champs, interprétés comme des tempêtes, sont des amplifications contrôlées et bi-variés d'épisodes extrêmes déjà observés. Ils forment donc des tempêtes encore plus extrêmes. Les tempêtes simulées à une intensité contrôlée alimentent des modèles physiques événementiels à la côte, permettant d'aider les décideurs à l'anticipation de ces risques encore non observés.Enfin et depuis la construction de ces scenarii extrêmes, nous abordons la notion de pré-calcul dans le but d'apporter en quasi-temps réel au décideur et en tant de crise une prévision sur le risque littoral.L’ensemble de ce travail s'inscrit dans le cadre d'un besoin industriel d’aide à la modélisation physique : chainage de modèles numériques et statistiques. La dimension industrielle de cette thèse est largement consacrée à la conception et au développement d’un prototype de plateforme de modélisation permettant l’utilisation systématique d’un calculateur HPC pour les simulations et le chainage de modèles de façon générique.Autour de problématiques liées à la gestion du risque littoral, cette thèse démontre l'apport d'un travail de recherche à l'interface de plusieurs disciplines. Elle y répond en conciliant et proposant des méthodes de pointe prenant racine dans chacune de ces disciplines. / Studies and management of coastal hazards are of high concerns in our society, since they engage highly valuable economical and ecological stakes. Coastal hazards are generally responding to extreme environmental conditions. The study of these physical phenomena relies on the understanding of such environmental conditions, which are rarely (or even never) observed.In coastal areas, waves are the main source of energy. This energy is responsible of coastal hazards developed at different time-scales, like the submersion or the erosion.The presented work, taking place at the interface between Statistical Analysis, Geophysics and Computer Sciences, aiming at bringing forward tools and methods serving decision makers in charge of the management of such risks.In practice, the proposed solutions answer to the questionings with a consideration of the space dimension rather than only punctual aspects. This approach is more natural considering that environmental phenomena are generally spatial, as the sea-waves fields.The study of extreme realisations of such processes is based on the availability of a representative data set, both in time and space dimensions, allowing to extrapolating information beyond the actual observations. In particular for sea-waves fields, we use numerical simulation on high performance computational clusters (HPC) to product such a data set. The outcome of this work offers many application possibilities.Most notably, we propose from this data set two statistical methodologies, having respective goals of dealing with littoral hazards long-terms questionings (e.g., erosion) and event-scale questionings (e.g., submersion).The first one is based on the application of stochastic models so-called max-stable models, particularly adapted to the study of extreme values in a spatial context. Indeed, additionally to the marginal information, max-stable models allow to take into account the spatial dependence structures of the observed extreme processes. Our results show the interest of this method against the ones neglecting the spatial dependence of these phenomena for risk indices computation.The second approach is a semi-parametric method aiming at simulating extreme waves space-time processes. Those processes, interpreted as storms, are controlled and bi-variate uplifting of already observed extreme episodes. In other words, we create most severe storms than the one already observed. These processes simulated at a controlled intensity may feed littoral physical models in order to describe a very extreme event in both space and time dimensions. They allow helping decision-makers in the anticipation of hazards not yet observed.Finally and from the construction of these extreme scenarios, we introduce a pre-computing paradigm in the goal of providing the decision-makers with a real-time and accurate information in case of a sudden coastal crisis, without performing any physical simulation.This work fits into a growing industrial demand of modelling help. Most notably a need related to the chaining of numerical and statistical models. Consequently, the industrial dimension of this PhD.~is mostly dedicated to the design and development of a prototype modelling platform. This platform aims at systematically using HPC resources to run simulations and easing the chaining of models.Embracing solutions towards questionings related to the management of coastal hazard, this thesis demonstrates the benefits of a research work placed at the interface between several domains. This thesis answers such questionings by providing end-users with cutting-edge methods stemming from each of those domains.

Rip currents are the most dangerous hazard at surf beaches. Rip currents in South Florida have previously not been studied. Beach profiles for three Florida beaches (Miami Beach, Lido Beach, Sarasota, and Pensacola Beach) and one Georgia beach (South Cumberland Island) were chosen for surveying because of their variable sand bar heights. Rip current hazard at each beach was assessed by lifeguard rip rescue and drowning statistics. A relationship was found between sand bar height, beach slope and rip current hazard. Rip current measurements in South Florida, which involved utilizing GPS drifters, laser rangefinder and drone-imaged fluorescent tracer dye, showed that the speed ranged from 0.1-0.5 m/s, which is fairly slow compared to such measurements undertaken in California and Australia. The effect of rip currents on swimmers was analyzed based on the drag force acting on swimmers and the power they generate to overcome the currents when swimming against them. The drag force and power increase quadratically and cubically, respectively, with the increase of rip current and swimming speeds. Hence, even rip currents of low velocity can be dangerous and swimming against the current should be avoided if possible. Strong rips in California have been shown to exhibit a circulatory pattern, which could bring a floater back to the safety of a shallow sand bar. Field measurements of rip currents in South Florida clearly defined the flow characteristics of a nearly straight-line current, sometimes deflected to the east-southeast. Therefore, the traditional approach of swimming left or right, parallel to the shore is the best escape strategy, but not against the longshore current if present. A logistic regression analysis was conducted to predict the occurrence of rip currents based on beach conditions. The logistic model showed that wave height, wave period and wind speed were statistically significant factors in rip generation. Rips were found to be most commonly generated by relatively small, non-threatening waves (e.g., 0.6 to 0.9m in height). These physical factors, along with social and safety considerations, pose a significant problem for coastal management.