Ben Gouldby

The joint probability of waves and water levels in coastal engineering design

On coasts with high tidal ranges, or subject to high surges, both still water levels and waves can be important in assessing flood risk; their relative importance depends on location and on the type of sea defence. The simultaneous occurrence of large waves and a high still water level is therefore important in estimating their combined effect on sea defences. Wave period can also be important in assessing run-up and overtopping, and so it is useful also to have information on the joint distribution of wave height and period. Unless the variables are either completely independent or completely dependent, multivariate extremes are difficult to predict directly from observational data, as there may be too few events of the relevant type amongst the observations. In the past, the fitting and extrapolation of the dependence functions between the variables has often involved complicated and/or subjective approaches. This paper presents a method for joint probability analysis, using a Monte Carlo simulation approach, based on distributions fitted to water level, wave height and wave steepness, and to the dependence between them.

Flood early warning system: design, implementation and computational modules

We present a prototype of the flood early warning system (EWS) developed within the UrbanFlood FP7 project. The system monitors sensor networks installed in flood defenses (dikes, dams, embankments, etc.), detects sensor signal abnormalities, calculates dike failure probability, and simulates possible scenarios of dike breaching and flood propagation. All the relevant information and simulation results are fed into an interactive decision support system that helps dike managers and city authorities to make informed decisions in case of emergency and in routine dike quality assessment. In addition to that, a Virtual Dike computational module has been developed for advanced research into dike stability and failure mechanisms, and for training the artificial intelligence module on signal parameters induced by dike instabilities. This paper describes the UrbanFlood EWS generic design and functionality, the computational workflow, the individual modules, their integration via the Common Information Space middleware, and the first results of EWS monitoring and performance benchmarks.

Adaptive Flood Risk Management Under Climate Change Uncertainty Using Real Options and Optimization

It is well recognized that adaptive and flexible flood risk strategies are required to account for future uncertainties. Development of such strategies is, however, a challenge. Climate change alone is a significant complication, but, in addition, complexities exist trying to identify the most appropriate set of mitigation measures, or interventions. There are a range of economic and environmental performance measures that require consideration, and the spatial and temporal aspects of evaluating the performance of these is complex. All these elements pose severe difficulties to decisionmakers. This article describes a decision support methodology that has the capability to assess the most appropriate set of interventions to make in a flood system and the opportune time to make these interventions, given the future uncertainties. The flood risk strategies have been explicitly designed to allow for flexible adaptive measures by capturing the concepts of real options and multiobjective optimization to evaluate potential flood risk management opportunities. A state-of-the-art flood risk analysis tool is employed to evaluate the risk associated to each strategy over future points in time and a multiobjective genetic algorithm is utilized to search for the optimal adaptive strategies. The modeling system has been applied to a reach on the Thames Estuary (London, England), and initial results show the inclusion of flexibility is advantageous, while the outputs provide decisionmakers with supplementary knowledge that previously has not been considered.

Multiobjective Optimization for Improved Management of Flood Risk

Effective flood risk management requires consideration of a range of different mitigation measures. Depending on the location, these could include structural or non-structural measures as well as maintenance regimes for existing levee systems. Risk analysis models are used to quantify the benefits, in terms of risk reduction, when introducing different measures; further investigation is required to identify the most appropriate solution to implement. Effective flood risk management decision making requires consideration of a range of performance criteria. Determining the better performing strategies, according to multiple criteria can be a challenge. This paper describes the development of a decision support system that couples a multi-objective optimisation algorithm with a flood risk analysis model and an automated cost model. The system has the ability to generate potential mitigation measures that are implemented at different points in time. It then optimises the performance of the mitigation measures against multiple criteria. The decision support system is applied to an area of the Thames Estuary and the results obtained demonstrate the benefits multiobjective optimisation can bring to flood risk management.

Spatial and temporal analysis of extreme sea level and storm surge events around the coastline of the UK

In this paper we analyse the spatial footprint and temporal clustering of extreme sea level and skew surge events around the UK coast over the last 100 years (1915–2014). The vast majority of the extreme sea level events are generated by moderate, rather than extreme skew surges, combined with spring astronomical high tides. We distinguish four broad categories of spatial footprints of events and the distinct storm tracks that generated them. There have been rare events when extreme levels have occurred along two unconnected coastal regions during the same storm. The events that occur in closest succession (<4 days) typically impact different stretches of coastline. The spring/neap tidal cycle prevents successive extreme sea level events from happening within 4–8 days. Finally, the 2013/14 season was highly unusual in the context of the last 100 years from an extreme sea level perspective.

Multiscale modelling in real-time flood forecasting systems: From sand grain to dike failure and inundation

Abstract Severe events around the globe have highlighted the threat to life, infrastructure and the environment posed by flooding. Flood forecasting systems are a vital component of broader flood risk management activities. These systems are becoming increasingly more sophisticated as their importance in reducing life loss and economic damages is realized. Part of this increase in complexity is focused on the ability to predict and warn of failures in dykes, levees and embankments. A new European ICT project, UrbanFlood for Environmental Services and Climate Change Adaptation, has recently been commissioned and is introduced in this presentation. The primary objective of the Urban Flood project is to develop early warning systems that will monitor flood protection systems in real-time, identify vulnerable locations, model the failure and predict dike collapse and subsequent inundation. In combination with the damage assessment, Urban Flood will serve as an advanced decision support system, mitigating the impact of seasonal and catastrophic floods. Modeling is one of the key tasks in the project. The models will be required to simulate the behavior of the material properties of the layered dikes (sand, clay, peat, grass or concrete cover, metal frame, dam gates, etc.), during extreme hydraulic loading events. In earthen dikes, extra challenge is posed by the non-linear elastic plastic properties of the deformable clay. A realistic simulation of the dike will model the free-surface water dynamics; convective and diffusive transfer of water inside the porous materials; dynamic response of clay to the water pressure; structural mechanics, deformation and actual dike breakdown and flood. The models shall cover a wide range of scales from a sand grain to a flooded city. The time scales will range from seconds (for water penetrating the soil) to hours (for dike collapse dynamics and ocean tides). Eventually, the models will predict the influence of seasonal and global changes on the stability of flood defense systems. Full 3D transient simulation of dike failure with subsequent inundation will require significant computing resources. The project started three months ago, and we will present the plan for developing the modeling cascade for the system. This work is supported by the UrbanFlood European Union project N 248767, theme ICT-2009.6.4

Technical Note: Comparison of methods for threshold selection for extreme sea levels

Extreme value analysis is an important tool for studying coastal flood risk, but requires the estimation of a threshold to define an ‘extreme’, which is traditionally undertaken visually. Such subjective judgement is not accurately reproducible, so recently a number of quantitative approaches have been proposed. This paper therefore reviews existing methods, illustrated with coastal tide-gauge data and the Generalized Pareto Distribution, and proposes a new automated method that mimics the enduringly popular visual inspection method. In total, five different types of statistical threshold selection and their variants are evaluated by comparison to manually derived thresholds, demonstrating that the new method is a useful, complementary tool.

Exploring the Potential for Multivariate Fragility Representations to Alter Flood Risk Estimates: Potential for Multivariate Fragility Representations to Alter Flood Risk Estimates

In flood risk analysis, limitations in the multivariate statistical models adopted to model the hydraulic load have restricted the probability of a defense suffering structural failure to be expressed conditionally on a single hydraulic loading variable. This is an issue at the coastal level where multiple loadings act on defenses with the exact combination of loadings dictating their failure probabilities. Recently, a methodology containing a multivariate statistical model with the flexibility to robustly capture the dependence structure between the individual loadings was used to derive extreme nearshore loading conditions. Its adoption will permit the incorporation of more precise representations of a structures vulnerability in future analyses. In this article, a fragility representation of a shingle beach, where the failure probability is expressed over a three-dimensional loading parameter space-water level, wave height, and period-is derived at two localities. Within the approach, a Gaussian copula is used to capture any dependencies between the simplified geometric parameters of a beachs shape. Beach profiles are simulated from the copula and the failure probability, given the hydraulic load, determined by the reformulated Bradbury barrier inertia parameter model. At one site, substantial differences in the annual failure probability distribution are observed between the new and existing approaches. At the other, the beach only becomes vulnerable after a significant reduction of the crest height with its mean annual failure probability close to that presently predicted. It is concluded that further application of multivariate approaches is likely to yield more effective flood risk management.

Stochastic generation of spatially coherent river discharge peaks forlarge-scale, event-based flood risk assessment

Flood risk assessments are required for long-term planning, e.g. for investments in infrastructure and other urban capital. Vorogushyn et al. (2018) call for new methods in large-scale ‘Flood Risk Assessment’ (FRA) to enable the capturing of system interactions and 5 feedbacks. With the increase of computational power, large-scale, continental FRAs have recently become feasible (Ward et al., 2013; Alfieri et al., 2014; Dottori et al., 2016; Vousdoukas, 2016; Winsemius et al., 2016; ?) . ::: We ::::::: present : a :::: new ::::::: method :: to :::::::: generate :::::::: spatially ::::::: coherent :::: river :::::::: discharge ::::: peaks :::: over :::::::: multiple :::: river :::::: basins, :::::: which ::: can 10 :: be :::: used ::: for ::::::::::: event-based :::::::::: probabilistic ::::: flood :::: risk ::::::::: assessment :: on :: a :::::::::::::: continental-scale. ::: We :::: first :::::: extract ::::::: extreme :::::: events :::: from :::: river :::::::: discharge :::: time ::::: series :::: data :::: over :: a :::: large ::: set ::: of ::::::: locations :: by :::::::: applying ::::: new :::::::::::::::: peak-identification :::: and ::::::::::::: peak-matching ::::::: methods. ::::: Then ::: we ::::::: describe ::::: these ::::: events ::::: using ::: the :::::::: discharge 15 :::: peak :: at ::::: each :::::::: location, ::::: whilst :::::::::: accounting ::: for :::: the ::: fact :::: that :: the ::::::: events ::: do ::: not :::::: affect ::: all ::::::::: locations. :::::: Lastly ::: we ::: fit ::: the :::::::::::: state-of-the-art :::::::::: multivariate ::::::: extreme ::::: value ::::::::: distribution :: to ::: the :::::::: discharge ::::: peaks, :::: and ::::::: generate ::::: from ::: the ::::: fitted ::::: model :: a :::: large :: set ::: of ::::::: spatially :::::::: coherent :::::::: synthetic :::::: events. :::: We :::::::::: demonstrate 20 :: the ::::::::: capability ::: of :::: this :::::::: approach :: in ::::::::: capturing ::: the :::::::: statistical ::::::::: dependence ::::: over :: all :::::::::: considered :::::::: locations. :::: We :::: also :::::: discuss :: the ::::::::: limitations ::: of ::: this :::::::: approach ::: and ::::::::: investigate ::: the :::::::: sensitivity :: of ::: the ::::::: outcome :: to :::::: various :::::: model :::::::::: parameters. Copyright statement. The author’s copyright for this publication is 25 transferred to HR Wallingford, Deltares and GfZ.