Tsunami and storm surge are two of the main destructive and costly natural hazards faced by coastal communities around the world. To enhance coastal resilience and to develop effective risk management strategies, accurate and efficient tsunami and storm surge prediction models are needed. However, existing physics-based numerical models have the disadvantage of being difficult to satisfy both accuracy and efficiency at the same time. In this dissertation, several surrogate models are developed using statistical and machine learning techniques that can rapidly predict a tsunami and storm surge without substantial loss of accuracy, with respect to high-fidelity physics-based models. First, a tsunami run-up response function (TRRF) model is developed that can rapidly predict a tsunami run-up distribution from earthquake fault parameters. This new surrogate modeling approach reduces the number of simulations required to build a surrogate model by separately modeling the leading order contribution and the residual part of the tsunami run-up distribution. Secondly, a TRRF-based inversion (TRRF-INV) model is developed that can infer a tsunami source and its impact from tsunami run-up records. Since this new tsunami inversion model is based on the TRRF model, it can perform a large number of tsunami forward simulations in tsunami inversion modeling, which is impossible with physics-based models. And lastly, a one-dimensional convolutional neural network combined with principal component analysis and k-means clustering (C1PKNet) model is developed that can rapidly predict the peak storm surge from tropical cyclone track time series. Because the C1PKNet model uses the tropical cyclone track time series, it has the advantage of being able to predict more diverse tropical cyclone scenarios than the existing surrogate models that rely on a tropical cyclone condition at one moment (usually at or near landfall). The surrogate models developed in this dissertation have the potential to save lives, mitigate coastal hazard damage, and promote resilient coastal communities. / Doctor of Philosophy / Tsunami and storm surge can cause extensive damage to coastal communities; to reduce this damage, accurate and fast computer models are needed that can predict the water level change caused by these coastal hazards. The problem is that existing physics-based computer models are either accurate but slow or less accurate but fast. In this dissertation, three new computer models are developed using statistical and machine learning techniques that can rapidly predict a tsunami and storm surge without substantial loss of accuracy compared to the accurate physics-based computer models. Three computer models are as follows: (1) A computer model that can rapidly predict the maximum ground elevation wetted by the tsunami along the coastline from earthquake information, (2) A computer model that can reversely predict a tsunami source and its impact from the observations of the maximum ground elevation wetted by the tsunami, (3) A computer model that can rapidly predict peak storm surges across a wide range of coastal areas from the tropical cyclone's track position over time. These new computer models have the potential to improve forecasting capabilities, advance understanding of historical tsunami and storm surge events, and lead to better preparedness plans for possible future tsunamis and storm surges.

Coastal foredunes are natural aeolian bedforms located landward of the backshore and which interact continuously with the beach. Traditionally, coastal dunes have been associated with onshore winds, however they can be found under more complex wind regimes where offshore winds are common such as the UK East coast, Northern Ireland and New Zealand. This research investigates the ways in which foredune-beach interactions occur under a complex wind regime at a range of overlapping temporal and spatial scales and is innovative in that it explicitly links small-scale processes and morphodynamic behaviour to large scale and long-term dynamics. The study area is the north Lincolnshire coast, East England. Detailed observations of airflow at three locations under varying wind regimes revealed considerable spatial variations in wind velocity and direction, however it was possible to determine a general model of how foredune topography deflected and modified airflow and the resultant geomorphological implications (i.e. erosion and deposition). During direct offshore and onshore winds, airflow remained attached and undeflected; and distinct zones of flow deceleration and acceleration could be identified. During oblique winds airflow was deflected to become more parallel to the dune crest. The field sites used are characterized by a seasonal erosion/accretion cycle and a series of increasingly complex models was developed and tested to determine whether it was possible to predict sand volume changes in the foredune-beach system based on a limited number of variables. The model predictions were tested against detailed digital terrain models at a seasonal timescale. The model prediction that best matched the observed (surveyed) sand volume changes included wind speed, direction, grain size, fetch effect controlled by beach inundation and angle of wind approach was accurate to within ±10% for 18 out of 48 tests at the seasonal scale and 6 out of 12 tests over periods of >5 years. A key variable influencing foredune-beach sand volume is the magnitude and frequency of storm surge events and this was not factored in to the model, but may explain the model-observation mismatch over the medium-term on two occasions. Over the past 120 years historical maps and aerial photographs indicate long-term foredune accretion of approximately 2 m year-1 at the three study sites (1891-2010). At this timescale, rates of coastal foredune accretion reflect the low occurrence of severe storm surges and suggest rapid post-storm recovery. The morphological response of the foredune-beach morphology is considered to be a combination of controlling and forcing factors. Process-responses within the system, associated with nearshore interactions and sediment transfer from the littoral drift, are compiled into a multi-scale morphodynamic model. Important to match appropriate dataset to scale of research question or management plan being explored. In the case of management, long-term records of past activity are necessary to predict the future but also to understand natural responses of system to short-term impact such as storm surge.

A hurricane is a combination of sustained winds, low atmospheric pressures and precipitation. Over the past decades, Louisiana has experienced several devastating hurricanes. The east bank of the City of New Orleans is bounded by Lake Pontchartrain to the North and the Mississippi River to the South. Lake Pontchartrain is a brackish system connected to the Gulf of Mexico through Lake Borgne to the East. As a Hurricane enters the Estuary from the Gulf of Mexico, it imposes a sustained surge of a few meters which may lead to flooding in areas which are not protected by levees. These flood water may be saline. Saltwater flooding is an environmental issue in flooded marshlands since saltwater can be fatal to some plants. The response of salinity and storm surge to hurricane duration which represents the forward speed of the storm is numerically modeled.

The United States coastline contain some of the most valued ecological resources, the most populated urban areas, the most complex infrastructure systems, the most prolific economic engines, and the busiest ports of trade. However important the coastline may be to our nation, the history of our coastal communities suggests that they are extremely vulnerable to natural disasters, including hurricane landfall. There are many potential reasons for this vulnerability, and several of them are considered in this work. The common goal of research presented here is to better understand the hydrodynamic forces developed as hurricanes impact the coast so that the resulting effects on coastal resources can be better understood and managed, and vulnerability can be significantly minimized. This work begins with consideration of the hydraulic domain at the interface between inland riverine and coastal environments. Regulators, and therefore those being regulated, generally prefer to separate riverine systems from coastal systems in the design and analysis of coastal infrastructure. Although analysis is greatly simplified, important synergistic hydrodynamic effects are not considered which can have dramatic negative effects on the ability of infrastructure to withstand hurricane impact. Research continues by evaluating how society delineates the coastal flood hazard. Current methods apply a deterministic, steady-state approach to defining this highly dynamic feature influenced by multiple uncertain and variable parameters. By ignoring the variability inherent in the coastal floodplain, society is not able to correctly define the flood hazard, and therefore cannot fully asses the risk to which it is exposed. A methodology is presented to more realistically quantify the coastal flood hazard and to calculate an appropriate flood risk metric. Finally, this research considers the reliability of a coastal community's water distribution system under hurricane impact. By understanding system vulnerability and system interdependence, community leaders can provide more reliable infrastructure systems, thereby reducing the magnitude of disaster and shortening the recovery time. A methodology is presented to quantify the reliability of a water system under several hurricane impact scenarios.

The topographical variations of the seas around Taiwan are great, which make the tides complicated. Taiwan is located in the juncture of the tropical and subtropical area. Geographically, it is located within the region of northwestern Pacific typhoon path. These seasonal and geographical situations causing Taiwan frequently threaten by typhoons during summer and autumn. In addition to natural disasters, the coastal area is over developed for the last few decades, which destroys the balance between nature and man. Storms and floods constantly threaten the lowland areas along the coast. An accurate and efficient storm surge model can be used to predict tides and storm surges. The model can be calibrated and verified with the field observations. Data measured by instruments at the tidal station constituting daily tidal variations and storm surge influences during typhoons. The model can offer both predictions to the management institutions and to the general public as pre-warning system and thus taking disaster-prevention measures. This study implements the numerical model, developed by Yu (1993) and Yu et al. (1994) to calculate the hydrodynamic in the seas around Taiwan. The main purpose of this study is to make a calibration and sensitivity analysis of the model parameters. Tidal gauge data around Taiwan coastal stations collected from June to October 2005 are used for the analysis and the comparison between the modeled data and the observations. Two steps have been taken for the model calibration and sensitivity analysis. First step is to calibrate the model for accurate prediction of the astronomical tide, and then the compound tide with meteorological influences. For the calibration of the astronomical tides, sensitivity analysis has been carried out by adjusting the horizontal diffusion coefficient and the bottom friction coefficients used in the model. The sensitivity of the time-step size used in the model and model grids fitted to coastlines are also checked. A depth dependent Chézy numbers are used in the model to describe bottom friction. The model has a better result when the Chézy value varied within 65 to 85. Modifying grids fitted to the coastline has improved the model results significantly. By improving the dynamic phenomenon brought about by the land features, the model calculation fits the real tidal phenomenon better. The analysis has shown that the model is less sensitive to the horizontal diffusion coefficient. Data from 22 tidal stations around Taiwan have been used for the comparisons. The maximum RMSE (root-mean-square error) is about 10 cm at WAi-Pu, whereas the minimum RMSE is about 1 cm for the stations along eastern coast. The calibration of the compound tide is divided into three cases. The first case is to calibrate the forecasted wind field. This has been done by comparing the forecasted wind field from the Central Weather Bureau with the satellite data obtained from QuikSCAT¡XLevel 3. The satellite wind speed has been applied to adjust the forecasted wind speed. The adjusted forecast wind field has shown improvement to the model predictions in the tidal stations south of Taichung, slightly improved in the eastern coast. The second case is tuning the drag coefficient on sea surface used by the hydrodynamic model. Several empirical formulas to describe the sea surface drag have been tested. The model result has shown little influence using various drag formulations. The third case is to single the influences by the meteo-inputs, i.e. the wind field and the atmospheric pressure. The tidal level is more sensitive to the variation of the atmospheric pressure through out the tests carried out during typhoon periods. The model simulation for 2006 using the best selected parameters has shown that the model is consisted with good stability and accuracy for both stormy and calm weather conditions.

Recent events such as the New Orleans floods and the Japanese tsunami of 2011 have highlighted the uncertainty in the quantification of the magnitude of natural hazards. The research undertaken here has focussed on the uncertainty in evaluating storm surge magnitudes based on a range of statistical techniques including the Generalised Extreme Value distribution, Joint Probability and Monte Carlo simulations. To support the evaluation of storm surge frequency magnitude relationships a unique hard copy observed sea level data set, recording hourly observations, was acquired and digitised for Devonport, Plymouth, creating a 40 year data set. In conjunction with Devonport data, Newlyn (1915-2012) tide gauge records were analysed, creating a data set of 2 million data points. The different statistical techniques analysed led to an uncertainty range of 0.4 m for a 1 in 250 year storm surge event, and 0.7 m for a 1 in 1000 storm surge event. This compares to a 0.5 m uncertainty range between the low and high prediction for sea level rise by 2100. The Geographical Information system modelling of the uncertainty indicated that for a 1 in 1000 year event the level uncertainty (0.7 m) led to an increase of 100% of buildings and 50% of total land affect. Within the study area of south-west England there are several critical structures including a nuclear licensed site. Incorporating the uncertainty in storm surge and wave height predictions indicated that the site would be potentially affected today with the combination of a 1 in 1000 year storm surge event coincident with a 1 in 1000 wave. In addition to the evaluation of frequency magnitude relations this study has identified several trends in the data set. Over the data period sea level rise is modelled as an exponential growth (0.0001mm/yr2), indicating the modelled sea level rise of 1.9 mm/yr and 2.2 mm/yr for Newlyn and Devonport, will potentially increase over the next century by a minimum of 0.2 m by 2100.The increase in storm frequency identified as part of this analysis has been equated to the rise in sea level, rather than an increase in the severity of storms, with decadal variations in the observed frequency, potentially linked to the North Atlantic Oscillation. The identification as part of this study of a significant uncertainty in the evaluation of storm surge frequency magnitude relationships has global significance in the evaluation of natural hazards. Guidance on the evaluation of external hazards currently does not adequately consider the effect of uncertainty; an uncertainty of 0.7 m identified within this study could potentially affect in the region of 500 million people worldwide living close to the coast.

The following presents a method for determining topographic elevation error for overland unstructured finite element meshes derived from bare earth LiDAR for use in a shallow water equations model. This thesis investigates the development of an optimal interpolation method to produce minimal error for a given element size. In hydrodynamic studies, it is vital to represent the floodplain as accurately as possible since terrain is a critical factor that influences water flow. An essential step in the development of a coastal inundation model is processing and resampling dense bare earth LiDAR to a DEM and ultimately to the mesh nodes; however, it is crucial that the correct DEM grid size and interpolation method be employed for an accurate representation of the terrain. The following research serves two purposes: 1) to assess the resolution and interpolation scheme of bare earth LiDAR data points in terms of its ability to describe the bare earth topography and its subsequent performance during relevant tide and storm surge simulations

Dentre os ambientes costeiros, os estuários são as principais fontes de sedimento para os oceanos. Sua dinâmica sensível é amplamente suscetível a modificações de origem natural e antrópica impactando no balanço sedimentar destes ambientes. O presente trabalho busca compreender a importância da maré meteorológica causada por frentes frias sobre os processos sedimentares do complexo estuarino de Santos aplicando o modelo numérico XBeach com três cenários. O primeiro foi forçado apenas pela maré astronômica outro representando uma condição de frente fria média e um terceiro representando uma frente fria extrema. Buscou-se detectar as frentes utilizando dados de reanálise do NCEP/NCAR. Foram extraídos os cinco dias mais intensos das frentes escolhidas e aplicaram-se ao inicio da série de dados de input do modelo para os ensaios numéricos. Os resultados permitiram compreender que os sistemas frontais atuam como agentes essenciais no balanço sedimentar tendo um papel erosivo compensando os processos deposicionais atuantes no período sem frentes. Frentes muito intensas agravam as feições erosivas e deposicionais, desbalanceando o sistema além da sua capacidade de recuperação. / Among the coastal environments, the estuaries are the main sediment source for oceans. Its sensible dynamic is widely susceptible to changes of natural and anthropogenic impacts the sediment balance of those environments. This work applies the Xbeach numerical model in Santos estuary to understand the storm surges forced by cold fronts on the sediment transport through three scenarios. The first scenario input was astronomic tide sea surface high, the second scenario input was the median cold front and the last scenario input was an extreme cold front. To get the cold front condition we use the NCEP/NCAR reanalysis data. We applied the five most intense days from each cold front condition in the beginning astronomic tide series. With the numerical model results we could understand the erosive action from the cold fronts and how it compensates the depositional period without any cold fronts. The extreme cold fronts intensify the depositional/erosion process unbalancing the system beyond the resilience capacity.

Marsh vegetation is widely considered to offer protection against coastal storm damage, and vegetated flow has thus become a key area of hydrodynamic research. This study investigates the utility of simulated Spartina alterniora marsh vegetation as storm protection using an ADV measurement technique, and is the first to apply jet self-similarity analysis to characterize the overall mean and turbulent flow properties of a three-dimensional axisymmetric jet through a vegetated array. The mean axial flow of a horizontal axisymmetric turbulent jet is obstructed by three configurations of staggered arrays of vertical rigid plant stems. The entire experiment is repeated over five sufficiently high jet Reynolds number conditions to ensure normalization and subsequent collapse of data by nozzle velocity so that experimental error is obtained. All self-similarity parameters for the unobstructed free jet correspond to typical published values: the axial decay coefficient B is 5:8 +/- 0:2, the Gaussian spreading coefficient c is 85 +/- 5, and the halfwidth spreading rate eta_(1/2) is 0:093 +/- 0:003. Upon the introduction of vegetation, from partially obstructed to fully obstructed, B falls from 5:1+/- 0:2 to 4:2 +/- 0:2 and finally 3:7 +/-0:1 for the fully obstructed case, indicating that vegetation reduces axial jet velocity. Cross-sectionally averaged momentum for the unobstructed free jet is M=M0 = 1:05 +/- 0:07, confirming conservation of momentum. Failure of conservation of momentum is most pronounced in the fully obstructed scenario – M=M0 = 0:54 +/- 0:05. The introduction of vegetation increases spreading of the impinging jet. The entrainment coefficient alpha for the free jet case is 0.0575; in the fully obstructed case, alpha = 0:0631. Mean advection of mean and turbulent kinetic energy demonstrates an expected reduction in turbulence intensity within the vegetated array. In general, turbulent production decreases as axial depth of vegetation increases, though retains the bimodal profile of the free jet case; the fully vegetated case, however, exhibits clear peaks behind plant stems. Turbulent transport was shown to be unaffected by vegetation and appears to be primarily a function of axial distance from the jet nozzle. An analysis of rate of dissipation revealed that not only does the cumulative effect of upstream wakes overall depress the magnitude of spectral energy density across all wavenumbers but also that plant stems dissipate large anisotropic eddies in centerline streamwise jet flow. This study, thus, indicates that sparse emergent vegetation both reduces axial flow velocity and has a dissipative effect on jet flow. Typically, however, storm surge does not exhibit the lateral spreading demonstrated by an axisymmetric jet; therefore, the results of this study cannot conclusively support the claim that coastal vegetation reduces storm surge axial velocity.

学位授与大学：京都大学 ; 取得学位: 博士(工学) ; 学位授与年月日: 2007-09-25 ; 学位の種類: 新制・課程博士 ; 学位記番号: 工博第2844号 ; 請求記号: 新制/工/1418 ; 整理番号: 25529 / An atmosphere-ocean coupled model was developed based on a preexisting non-hydrostatic mesoscale atmosphere model (MM5) and non-hydrostatic ocean circulation model (MITgcm). This model together with a pre-established wind-wave-currents coupled model was applied to a number of regional environmental issue and disaster events to reproduce the present status and past situations and to help our understanding of the physical processes of such problems in terms of atmosphere-ocean interactions including the sea surface waves in the interface between air and sea. The disaster events and environmental issue studied in this thesis are follows. 1) Storm surge induced by Hurricane Katrina in the Gulf coast of USA in 2005. 2) Extreme high waves at Hara coast, Suruga Bay in Japan caused by the super-Typhoon TIP in 1979. 3) Positive and negative feedbacks in typhoon-ocean interaction in case of Typhoon ETAU in 2003. 4) Thermal water circulation in a dam-made lake (Yachiyo Lake) in Hiroshima, Japan concerning on the hydrodynamics in the lake. 5) Reanalysis of the past 47 storms that caused disasters in West Kyushu, Japan. 6) Wave overtopping simulation over through the submerged offshore breakwater and enhance seawall. The Regional Environment and Disaster Prevention Simulator is proposed and constructed based on the regional atmosphere-ocean coupled model in this thesis of which the objective was improvement of the numerical assessment method to disaster events and environment problems by introducing he coupling effects between different systems. / Kyoto University (京都大学) / 0048 / 新制・課程博士 / 博士(工学) / 甲第13373号 / 工博第2844号 / 新制||工||1418(附属図書館) / 25529 / UT51-2007-Q774 / 京都大学大学院工学研究科社会基盤工学専攻 / (主査)教授 関口 秀雄, 教授 間瀬 肇, 教授 中北 英一 / 学位規則第4条第1項該当