Thesis (Ph. D. (Statistics)) -- University of Limpopo, 2016. / Statistics of extremes has seen much growth both in theory and application since its early theoretical developments almost a century ago in the 1920s and its first major applications to real-life problems pioneered by Emil Gumbel in the early 1940s. Although the theory and applications of extreme value theory (EVT) have been extensively advanced and utilised in most developed countries,intermsofapplicationslittlehasbeendoneinmanydevelopingcountries in Africa despite the abundance of areas of applications and raw data in some ofthesecountries. Inhydrology,thechoiceoffloodfrequencyprobabilitydistributions for a particular site or region remains the subject of ongoing research. The work contained in this thesis is a contribution towards this area and it addresses this problem in one of the developing and economically challenged countries in Africa, Mozambique, in the lower Limpopo River basin (LLRB). The LLRB is a basin characterised by extreme natural hazards, alternating between extreme floods and severe droughts. ThisthesisisbasedonanextensiveapplicationofEVTtoextremefloodheights data in the LLRB of Mozambique at three sites: Chokwe, Combomune and Sicacate hydrometric stations. Two fundamental approaches of EVT, block maxima and peaks-over-threshold (POT), are used in this thesis. Recent theoretical results by Ferreira and de Haan (2015) have shown that despite its inefficiency due to data lost as a result of blocking, the block maxima approach is more efficient in a number of situations than the POT approach, and the two approaches are quite comparable for large sample sizes. A number of ii candidate distributions are investigated for their goodness-of-fit to the annual daily maximum flood heights in a block maxima realisation at each site. The findings reveal that the GEV distribution is the most appropriate distribution to apply in the LLRB and the distribution can be recommended as the likelihood function for regional and spatial extremes flood frequency analysis in the basin. The thesis addresses the issue of cumulative effects on daily flood heights through a comparative analysis of six annual maxima moving sums. The findings demonstrate that the six annual maxima time series models are notsignificantlydifferentbasedonthecharacteristicsconsideredinthisthesis. In an attempt to reduce uncertainties in the estimates, a Bayesian Markov chain Monte Carlo (MCMC) approach with a conjugate prior and a GEV likelihood function is used to model the tails of the extreme flood heights in the basin. The findings reveal that the addition of prior information in Bayesian MCMC substantially reduces uncertainties in the estimates and improves precision in the predicted extreme floods. The r largest order statistics models developed in this thesis are generally promising and the standard errors of the estimates of the parameters are substantially reduced. In order to account for climate change impact, nonstationary models are considered with the longterm trend and seasonal oscillation index (SOI) (a meteorological variable indicator) as covariates of the parameters of the GEV distribution and the generalised Pareto distribution (GPD). Among the major contributions of this thesis is a proposed procedure for the determination of the 8 days window period used in extracting independent r largest order values within the same year for the r largest order statistics approach. A summary of the key findings and contributions of this thesis are given in Chapter 9. Moreover, contributions by the study topic in each chapter are given at the end of each chapter. / DST-NRF Centre of Excellence in Mathematical and Statistical Sciences (CoEMaSS) of South Africa

Current U.S. Army Corps of Engineers water resources planning guidance directs the planners to consider all design alternatives with economic efficiency as the primary criterion. Recent criticism of the flood loss reduction planning is directed at the Corps. One criticism is that the traditional design practices of the Corps address only large flood events. The emphasis on large flood events precludes the use of nonstructural methods, whose economically feasible range is at smaller scales. However, the advantage of having nonstructural measures available to federal water resources planners is widely recognized. This study seeks to demonstrate that nonstructural means are at a disadvantage in the Corps planning process. It examines the institutional framework that directs the planning of these projects. Using data from Corps reports, the economically feasible ranges and optimal sizes are determined for selected nonstructural measures through a series of case studies. The resulting optimal sizes are compared to those recommended in the Corps reports. The optimal sizes of the nonstructural alternatives developed for this study are smaller than the recommended levels. In the current budget climate, the implementation of flood loss reduction projects may occur more frequently with the increased use of nonstructura1 measures since they require less investment. / Master of Science

This thesis examines the role of the public in Flood Risk Management (FRM) service provision at a time when the perceptions of the distribution of benefits provided by FRM interventions are in flux, and the role the public should play in FRM highly contested among stakeholders. Two schemes have marked the revised role of the public in FRM - Partnership Funding and Flood Re - both of which challenge existing judgments of the excludability and rivalry of benefits delivered by FRM interventions. The Partnership Funding scheme allocates capital for FRM projects proportionately to the public benefits they provide, allowing communities to top-up grants through local contributions. In comparison, by increasing accessibility to affordable insurance through cross-subsidies and pricing signals, Flood Re highlights a growing recognition that the distribution of gains as a result of widespread insurance uptake is greater than the benefits received by the policyholder alone. Following the identification of these schemes, we tested their social feasibility, examining both the scale and distribution of benefits. Due to the different stages of implementation of each scheme at the time of writing this thesis, two distinct methods were developed. The Partnership Funding Chapter used field data to examine how public-private funding of flood defences has changed service provision and the public acceptance of this transition. Whereas the Flood Re chapter used computer-based experiments to hypothesize how Flood Re may make the purchase of insurance a more or less attractive investment for different types of consumer. We found that Partnership Funding enabled more FRM projects to go ahead, raised public awareness of flood risk, and improved collaboration between stakeholders, but encouraged lower-cost projects, which, in the longer term, could transfer the expense of managing residual risk to the householder. In comparison, Flood Re provided peace of mind to householders struggling to afford rises in insurance premiums, but disproportionately benefited those who annually purchased insurance. Combining this proposed inequity in Flood Re with increasing residual risks, we identify a gap in service provision for the public who cannot afford household mitigation measures. We propose that loss mitigation and flood defence should become increasingly collaborative in line with the complexities of flooding within a community. We seek a move away from the information asymmetry which currently exists between insurance providers and policyholders, and yet simultaneously call for local authorities to recognise the capacity of the public to participate in FRM, and sustain resilience in the face of rising flood risk.

Universiẗat, Diss., 2006--Regensburg.

In recent years, coastal regions worldwide have experienced some of the most devastating hurricanes, such as Harvey and Ida, which resulted in immense human and capital loss. Unfortunately, global climate change, particularly sea-level rise, only amplifies their consequences since hurricanes and the associated storm-induced flooding become more frequent and deadlier. The goal of my work is to develop and implement tools towards effective strategies for resilient and sustainable cities, against storm hazards amidst climate change. We propose a comprehensive optimization framework to search, evaluate, and optimize over a multitude of potential solutions, under various budget and societal constraints. Our models yield significant monetary and efficiency improvements, and importantly, are created and updated based on stakeholders’ feedback (e.g., mayor’s office, transportation agencies, etc.). Case studies in New York City will be demonstrated.

Flash flood is among the most hazardous natural disasters, and it can cause severe damages to the environment and human life. Flash floods are mainly caused by intense rainfall and due to their rapid onset (within six hours of rainfall), very limited opportunity can be left for effective response. Understanding the socio-economic characteristics involving natural hazards potential, vulnerability, and resilience is necessary to address the damages to economy and casualties from extreme natural hazards. The vulnerability to flash floods is dependent on both biophysical and socio-economic factors. This study provides a comprehensive assessment of socio-economic vulnerability to flash flood alongside a novel framework for flash flood early warning system. A socio-economic vulnerability index was developed for each state and county in the Contiguous United States (CONUS). For this purpose, extensive ensembles of social and economic variables from US Census and the Bureau of Economic Analysis were assessed. The coincidence of socio-economic vulnerability and flash flood events were investigated to diagnose the critical and non-critical regions. In addition, a data-analytic approach is developed to assess the interaction between flash flood characteristics and the hydroclimatic variables, which is then applied as the foundation of the flash flood warning system. A novel framework based on the D-vine copula quantile regression algorithm is developed to detect the most significant hydroclimatic variables that describe the flash flood magnitude and duration as response variables and estimate the conditional quantiles of the flash flood characteristics. This study can help mitigate flash flood risks and improve recovery planning, and it can be useful for reducing flash flood impacts on vulnerable regions and population.

Bibliography: leaves [175-181]

Thesis (M.S. - Hydrology and Water Resources)--University of Arizona, 1982. / Includes bibliographical references (leaves 136-142).

Thesis (M.E.S.)--The Evergreen State College, 2007. / Title from title screen (viewed 1/23/2008). "A thesis: essay of distinction submitted in partial fulfillment of the Master of Environmental Studies, The Evergreen State College, June 2007." Includes bibliographical references (leaves 66-70).

Thesis (M.Sc. (Geography)) -- University of Limpopo, 2019 / Floods are one of the major natural hazards that occur with devastating effects globally. South Africa is one of the countries that is affected as flooding frequently occurs at different sub-national scales and with devastating impacts on human settlements. The variability of the nature, impact and frequency of flood occurrence in the country has heightened interest in the assessment and determination of flooding vulnerability, particularly in areas that have been affected or are likely to be affected in the near future. Given the uncertainties surrounding flood occurrence and the enormous damages resulting from the events, this study sought to assess the vulnerability of settlements to floods in Ward 7 and 9 of Lephalale Local Municipality. To accomplish this, both primary and secondary sources of data were used in this study. A mixture of closed-ended and open-ended household questionnaire, which was administered to 133 and 227 randomly selected households in Ward 7 and 9 respectively was used. In addition, a vulnerability index was developed using an indicator approach in order to determine levels of flood vulnerability in the study areas. Indicators were identified, grouped and normalised using the standardization method, then weighted using pairwise comparison method. The various indicators were then aggregated through a linear summation method into a vulnerability index. This index was subsequently used to produce a vulnerability map showing the spatial pattern of the different flood vulnerability levels in the studied areas. The results reveal that socioeconomic as well as physical factors influence settlements’ vulnerability to flooding disasters. Furthermore, the vulnerability index map showed that Ward 7 was more vulnerable to flooding, with an average index of about 0.16 while Ward 9 was less vulnerable, with an average flood vulnerability index of 0,07. The vulnerability map also indicated that out of the total land area of 13.54km2 occupied by settlements in Ward 7, 9.38 km2 was very vulnerable, 2.27km2 highly vulnerable and 1.89km2 had low vulnerability. In Ward 9, about 4.44km2 of settlements land was experiencing low vulnerability while 29.96km2 experienced very low levels of vulnerability. The study concludes that the high vulnerability of Ward 7 was a result of an interplay of factors that include its nearness to the stream, a high proportion of low-lying land, land use type and high population densities. The results of this study can serve as a basis for targeting prioritization efforts, emergency response measures, and policy interventions at the ward level for minimizing flood disaster vulnerability in municipal areas. The study recommends that flood vulnerability assessments should integrate socio-economic characteristics with physical factors in order to adequately assess vulnerability and therefore enable municipalities to anticipate floods and plan for them. / University of Limpopo Staff Financial Assistance, Risk and Vulnerability Science Centre and VLIR