Tsunami are rare geological phenomena but their impacts are frequently catastrophic. Greece is the European country that has been affected most frequently by tsunami. Whilst tsunami hazard and risk within Greece have been studied, tsunami vulnerability has not. Previous studies and hazard mapping of tsunami flood prone areas around the world imply that populations, buildings and infrastructure within a potential inundation zone are uniformly vulnerable to impact. However, vulnerability is a dynamic factor and is a function of a number of parameters, since vulnerability of any physical, structural or socio-economic element is the probability of it being damaged, destroyed or lost. This dissertation identifies two coastal segments within Greece known to be at risk from tsunami flooding; reviews the historical record of events and determines a worse case tsunami event for both locations. A new methodology for assessing vulnerability of these coastal communities is then developed and applied to each location. The methodology incorporates multiple parameters that contribute to tsunami vulnerability and identifies and demonstrates the vulnerability of different components of the community (human, economic and the built environment). Using a Multi Criteria Evaluation Method the vulnerability of individual buildings and open spaces within the potential inundation zone are assessed and the results are displayed in map form with the aid of a Geographical Information System (GIS). The primary database may be used by various end-users, such as emergency planners, insurance companies, individuals, local authorities and scientists, in order to produce maps that could enable them to make recommendations regarding response plans or mitigation measures. Finally, a framework for Tsunami Vulnerability Assessment is introduced which integrates this vulnerability assessment methodology. Through this framework, the Greek Civil Protection system is outlined, its weaknesses are discussed and recommendations are made.

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The Denver Unit of Wasson Field, located in Gaines and Yoakum Counties in west Texas, produces oil from the San Andres dolomite at a depth of 5,000 ft. Wasson Field is part of the Permian Basin and is one of the largest petroleum-producing basins in the United States. This research used a modeling approach to optimize the existing carbon dioxide (CO2) flood in section 48 of the Denver Unit by improving the oil sweep efficiency of miscible CO2 floods and enhancing the conformance control. A full compositional simulation model using a detailed geologic characterization was built to optimize the injection pattern of section 48 of Denver Unit. The model is a quarter of an inverted nine-spot and covers 20 acres in San Andres Formation of Wasson Field. The Peng-Robinson equation of state (EOS) was chosen to describe the phase behavior during the CO2 flooding. An existenting geologic description was used to construct the simulation grid. Simulation layers represent actual flow units and resemble the large variation of reservoir properties. A 34-year history match was performed to validate the model. Several sensitivity runs were made to improve the CO2 sweep efficiency and increase the oil recovery. During this study I found that the optimum CO2 injection rate for San Andres Formation in the section 48 of the Denver Unit is approximately 300 res bbl (762 Mscf/D) of carbon dioxide. Simulation results also indicate that a water-alternating-gas (WAG) ratio of 1:1 along with an ultimate CO2 slug of 100% hydrocarbon pore volume (HCPV) willallow an incremental oil recovery of 18%. The additional recovery increases to 34% if a polymer is injected as a conformance control agent during the course of the WAG process at a ratio of 1:1. According to the results, a pattern reconfiguration change from the typical Denver Unit inverted nine spot to staggered line drive would represent an incremental oil recovery of 26%.

Detailed experiments were conducted on a meandering compound channel, with a sinuosity of 1.384, in a 13m long 2.4m wide flume. Two cases were examined, where the main channel contained flat and natural bedforms. Measurements recorded include stage-discharge, sediment transport and bed shear stress. A three-component Laser Doppler Anemometer measured the velocity and turbulence in the flow and the bedform was measured using Digital Photogrammetry. It was found from the stage-discharge data that at most depths the effect of the bedforms is to reduce the discharge capacity of the channel. The maximum reduction in the discharge capacity was at the bankfull flow depth where the discharge was reduced by thirty percent. The sediment transport rate was found to decrease at relative overbank flow depths of 0.2-0.3. The velocity and turbulence measurements were used to examine the flow structure. It was found that the formation of bedforms in the main channel significantly affects the flow structure of the flow in the main channel, although the flow on the floodplain is similar. Significant secondary flow circulations were found in the natural bed case, particularly at higher flow depths. The secondary circulations are caused by centrifugal force, flow entering the main channel from the floodplain and reverse flows as the flow passes over ridges in the natural bed case. A new method for predicting velocity and discharge in meandering channels has been introduced based on the two-dimensional curvilinear equations for strearnwise motion. The turbulence terms were found to be insignificant and the method was applied to data sets at different scales.

Water has always been an essential part of human life. It is necessary for every human activity and process. However, this life-sustaining resource can also cause mass destruction and loss of life. As populations grow and floods occur more frequently and at a larger scale, it becomes increasingly crucial to comprehend the variables and processes that surround flood events. Understanding these factors can help us mitigate the risks associated with floods and minimize their impact on communities. This dissertation consists of six chapters which cover two aspects of flooding. The first aspect deals with the sources of flooding events in a multi-regional basin. The second aspect concerns the impact of anthropogenic activity on flooding processes. In the first two chapters, the research motivation is presented, accompanied by a general review of the concepts that govern the research performed. Chapter three provides a statistical analysis of flood incidents based on their location and the prevailing weather conditions. The results of this chapter indicate that there has been a 6% annual increase in flooding each year across the basin of interest, with a staggering 770% increase in the last four years of the study. The main source of this increase is the lower level flood events, which are often the result of human development. Another notable observation in this chapter is that the majority of weather events that led to flooding were non-tropical in nature. Chapter four examines the relationship between land use and flooding by utilizing various statistical and machine learning techniques to identify the types of land use that contribute the most to flooding within the basin. Findings from this chapter include the loss of croplands across the entire basin, with an almost 1:1 replacement with open water surface and urban area, two land uses that produce the most runoff in precipitation events. In chapter five, we present a numerical model of the lower James River Basin in Virginia, which serves as a tool to assess the impact of land use modifications on flooding in the area. From 2004 to 2021, the basin lost over 13-million cubic meters of storage. Finally, chapter six provides an overview of future work and guidance in this area. / Doctor of Philosophy / Accurately predicting the severity and extent of floods is crucial for organizing activities such as evacuation, emergency response, and recovery planning. However, predicting floods can be a daunting task due to the countless basin configurations and various factors that need to be considered, such as slope, land use, development, and infrastructure. In some cases, numerical flood models can only be used in certain areas due to computational limitations, while in others, it may not be possible to use modeling at all. To tackle these challenges, traditional statistical tools can be used to provide information that can be incorporated into local numerical flood models. This text utilizes publicly available data in a series of statistical, machine learning, and numerical modeling tools to examine flooding in the James River Basin. The first three chapters provide a general overview and research motivation followed by a comprehensive history and statistical analysis of storms in the James River Basin over the last 70 years. The remaining three chapters present a method for assessing land use indicators of flooding using traditional statistics and machine learning tools. Finally, a numerical model of the coastal region of the James River Basin is presented, examining the interaction between the ocean and riverine environments during simulated events.

Flooding is a major obstacle for soybean production in the Mississippi Delta. One management practice that soybean producers use to mitigate the effects of flooding is planting soybean on raised beds. Another potential management practice that could be employed in the Mississippi Delta is the use of flood tolerant soybean cultivars. Therefore, the objective of this study was to evaluate the effectiveness of raised beds for flooding management and compare the tolerance of six soybean cultivars under flooded conditions at multiple growth stages and flood durations. Field studies were established during the 2017 and 2018 growing seasons at the Mississippi State Delta Research and Extension Center on a Sharkey clay soil. Treatments consisted of a factorial arrangement of six soybean cultivars, two flood timings (V4 and R2) and two flood durations (24 and 72 hours). Injury ratings were taken 7 DAT and 14 DAT. Seed yield was determined at harvest.

Waterflooding has been used for many decades as a way of recovering oil from petroleum reservoirs. Historically the salinity of the injection water has not been regarded as a key variable in determining the amount of oil recovered. In recent years, however, evidence of increased oil recovery by injection of low salinity water has been observed in laboratories and fields. The technique is getting wider attention in the oil industry because it is more cost-effective than other EOR techniques. The present work demonstrates the synergy of low salinity water flooding and polymer flooding in the laboratory scale. The use of low salinity polymer solution in polymer flooding has significant benefits because considerably lower amount of polymer is required to make the solution of a target viscosity. Low salinity polymer flooding can also increase oil recovery by lowering residual oil saturation and achieve faster oil recovery by improving sweep efficiency. Several coreflood experiments were conducted to study the efficiency of low salinity water flooding and low salinity polymer flooding in mixed-wet Berea sandstone cores. All the core samples were aged with a crude oil at 90oC for 30-60 days before the tests. All the polymer floods were conducted in the tertiary mode. A synthetic formation brine (33,800 ppm) was chosen for high salinity water and a NaCl brine (1,000 ppm) for low salinity water. Medium molecular weight HPAM polymer, FlopaamTM 3330S was used due to the low/moderate permeability of the Berea sandstone cores used in this study. Coreflood tests indicate that injection of low salinity polymer solution reduces residual oil saturation by 5-10% over that of the high salinity waterflood. A part of the residual saturation reduction is due to low salinity and this reduction is achieved in less pore volumes of injection in the presence of polymers. Effluent ion analysis from both low salinity water flooding and low salinity polymer flooding showed a slight increase in divalent cation concentrations after the polymer breakthrough. Cation bridging may play a role in oil wettability and low salinity injection desorbs some of these cations. / text

With the impact of global climate change, the speedy, intelligent and accessible dissemination of coastal flood predictions from a number of modelling tools at a range of temporal and spatial scales becomes increasingly important for policy decision makers. This thesis provides a novel approach to integrate the coastal flood data into an ArcFLOOD data model to improve the analysis, assessment and mitigation of the potential flood risk in coastal zones. This novel methodology has improved the accessibility, dissemination and visualisation of coastal flood risk. The results were condensed into spatial information flows, data model schematic diagrams and XML schema for end-user extension, customisation and spatial analysis. More importantly, software developers with these applications can now develop rich internet applications with little knowledge of numerical flood modelling systems. Specifically, this work has developed a coastal flooding geodatabase based upon the amalgamation, reconditioning and analysis of numerical flood modelling. In this research, a distinct lack of Geographic Information Systems (GIS) data modelling for coastal flooding prediction was identified in the literature. A schema was developed to provide the linkage between numerical flood modelling, flood risk assessment and information technology (IT) by extending the ESRI ArcGIS Marine Data Model (MDM) to include coastal flooding. The results of a linked hybrid hydrodynamic-morphological numerical flood model were used to define the time-series representation of a coastal flood in the schema. The results generated from GIS spatial analyses have improved the interpretation of numerical flood modelling output by effectively mapping the flood risk in the study site, with an improved definition according to the time-series duration of a flood. The improved results include flood water depth at a point and flood water increase which equates to the difference in significant wave height for each time step of coastal flooding. The flood risk mapping provided has indicated the potential risk to infrastructure and property and depicted the failure of flood defence structures. In the wider context, the results have been provided to allow knowledge transfer to a range of coastal flooding end-users.

As part of the effort to satisfy the ever increasing demand for a greater understanding of fluvial, hydrological, chemical, sedimentological and geomorphological processes operating on the floodplain, mathematical simulation models have come to play a significant role in the understanding, prediction and management of the floodplain environment. Underlying the accurate numerical representation of hydraulically driven processes is the provision of a suitable floodplain hydrology model which accounts for the interaction between surface hydraulics and subsurface hydrology. Such a numerical representation is currently not available at the spatial and temporal resolution required. It is the aim of this thesis to develop a novel conceptual approach to modelling floodplain hydrology in which the fundamental need to consider the interaction between surface and subsurface flow is the floodplain environment is addressed. This is achieved through the interactive coupling of a one-dimensional finite difference infiltration model with the state-of-the-art two-dimensional physically based finite element hydraulic model, TELEMAC2D. The coupled model provides an unparalleled spatial and temporal representation of surface and subsurface flow processes within the floodplain environment. The utility of this integrated approach is explored through an application of the model to two areas of contemporary floodplain research. In the first of these the model is run to assess the impact of infiltration on flood flow prediction for an llkm reach of the River Culm, UK, over a range of flood and soil conditions. In the second the model is run to investigate the nitrate buffering potential of floodplain riparian soils during flooding. For this investigation a model accounting for nitrate transport and denitrification is developed within the existing integrated hydraulic-infiltration model structure. An evaluation of the results from both of these investigations supports the need for a new approach to modelling fluvially driven floodplain processes which accounts for the spatially interactive nature of floodplain hydrology.

Urban drainage models are examined in terms of model purpose, type and usage. Model usage for the prediction of flooding behaviour in the UK adopts the design storm approach, which assumes that flood frequency equals rainfall frequency. This equation is shown to be affected by antecedent moisture conditions and rainfall spatial variability. Data collected from three small urban catchments (0.3 ha, 0.7 ha and 3.2 ha) in Southampton are used to calibrate and verify three urban drainage models: namely WASSP-SIM, WALLRUS-SIM and USGS-DR3M. A probabilistic approach to model verification is used and demonstrates that accepted bounds to model accuracy associated with the use of these models are difficult to justify if consideration is given to the possible errors in rainfall and discharge measurement. Comparison of the results from storms collected during 1985 on these catchments shows that the DR3M performs better than either of the other models in terms of a number of standard indices of model accuracy. Soil moisture observations collected over a two year period using the neutron probe method are then used to calibrate and test a number of simple soil moisture models including the soil moisture algorithm incorporated in the MORECS procedure and that included in the DR3M. These models are found to predict catchment average soil moisture conditions to within 20 mm, using local rainfall information and standard evapotranspiration curves as inputs. Using the MORECS soil moisture model it is shown that antecedent soil moisture conditions do have an impact on observed percentage runoff values, but that the relationship is confused by seasonal factors. The soil moisture model is then used together with WASSP-SIM to derive discharge-frequency curves using a continuous simulation approach. Comparisons with the design storm approach confirm the assumptions of the approach, although they do not prove that either approach produces the correct answers.