Flood vulnerability is quantified by loss models which are developed using either empirical or synthetic approaches. In reality, processes influencing flood risk stochastic and predictions bear significant uncertainty, especially due to differences in across exposed objects regions. However, many state-of-the-art deterministic, i.e., they do not account for data model uncertainty. The Bayesian ...

Floods cause environmental hazards and influence on socio-economic activities. In this study, we evaluated the historic flood frequency at a confluence in the middle Yellow River, China. A non-parametric, multivariate, empirical, orthogonal function matrix model, which consists of time correlation coefficients of flood discharge at different gauge stations and flood events was used for the anal...

Coastal cities are growing at a very rapid pace, both in population and in terms of assets; therefore, flood risk is likely to increase substantially in these areas in the absence of specific protections. In addition, great uncertainty surrounds the future evolution of hurricane intensity and sea level rise. The area of Miami represents a clear hotspot of human and economic coastal flood exposu...

In this paper, a non-cooperative two person zero-sum static game(with in a discrete interval of time) is formulated and analyzed for the interaction between the SYN flood attacker and the web server administrator. The SYN flood game (SFG) payoffs are calculated based on Erlang loss queuing model. The solution of the SFG leads to mixed strategy and analyzed for different scenarios the numerical ...

Traditional flood control systems always have a conflict with natural ones, i.e., rivers in cities are usually straight and smooth, whereas natural ones are according to ecological mechanisms. Social and economic developments in the modern world require a new system combining ecological needs and traditional flood control system. Ecological flood control systems were put forward and defined as ...

Risk-based approaches have been increasingly accepted and operationalized in flood risk management during recent decades. For instance, commercial flood risk models are used by the insurance industry to assess potential losses, establish the pricing of policies and determine reinsurance needs. Despite considerable progress in the development of loss estimation tools since the 1980s, loss estima...

Established in 1984, the Wharton Risk Management and Decision Processes Center develops and promotes effective corporate and public policies for low-probability events with potentially catastrophic consequences through the integration of risk assessment, and risk perception with risk management strategies. Natural disasters, technological hazards, and national and international security issues ...

This study applies Bayesian Inference to estimate flood risk for 53 dyke ring areas in the Netherlands, and focuses particularly on the data scarcity and extreme behaviour of catastrophe risk. The probability density curves of flood damage are estimated through Monte Carlo simulations. Based on these results, flood insurance premiums are estimated using two different practical methods that each...

Evidence is presented to show that there is a growing disparity between public perception and scientific evidence relating to the causes of floods, their impacts, and the benefits of mitigation measures. It is suggested that this disparity has arisen through the extensive promotion of certain land uses and engineering interventions by vested interest groups in the absence of any effective disse...

the management and analysis of flood hazards is of great socio- economic and ecological importance as it was estimated that 50 percent of word’s population resides and works within the costal zone till 2030. the management of coastal flood hazard reflects the cumulative effects and criteria more than the human mind can handle effectively. the flood management requires decision making for rela...