Abstract. Miami-Dade County (south-east Florida) is among the most vulnerable regions to sea level rise in United States, due a variety of natural and human factors. The co-occurrence multiple, often statistically dependent flooding drivers – termed compound events typically exacerbates impacts compared with their isolated occurrence. Ignoring dependencies between will potentially lead underestimation flood risk under-design defence structures. In water control structures were designed...

Abstract Compound flooding may result from the interaction of two or more contributing processes, which not be extreme themselves, but in combination lead to impacts. Here, we use statistical methods assess compounding effects storm surge and multiple riverine discharges Sabine Lake, TX. We employ several trivariate models, including vine‐copulas a conditional value model, examine sensitivity results choice data pre‐processing steps, model setup, outliers. define response function that...

Information on the wave climate at a particular location is essential in many areas of coastal engineering from design structures to flood risk analysis. It most commonly obtained either by direct measurements or hindcast meteorological data. The extended deployment buoy directly measure conditions and application transformation models used hindcasting, including public domain such as Wavewatch SWAN, are both expensive. accuracy results given latter also highly sensitive quality wind data...

Abstract Coastal areas are subject to the joint risk associated with rainfall‐driven flooding and storm surge hazards. To capture this dependency compound nature of these hazards, bivariate modelling represents a straightforward easy‐to‐implement approach that relies on observational records. Most existing applications focus single tide gauge–rain gauge/streamgauge combination, limiting applicability develop high‐resolution space–time design events can be used quantify dynamic, is, varying...

Flooding in low-lying coastal zones arises from (storm surge, tides, and waves), fluvial (excessive river discharge), pluvial surface runoff) drivers. We analyse changes compound flooding potential around the contiguous United States (CONUS) coastline stemming select combinations of these drivers using long observational records with at least 55 years data. assess temporal tail (extremal) dependence (χ) a 30-year sliding time window. Periods strong are found for windows centered between...

Abstract When different flooding drivers co‐occur, they can cause compound floods. Despite the potential impact of flooding, few studies have projected how joint probability may change. Furthermore, existing projections not be very robust, as are based on only 5 to 6 climate model simulations. Here, we use a large ensemble simulations from Coupled Model Intercomparison Project (CMIP6) project changes in extreme storm surges and precipitation at European tide gauges under medium high...

Two-sided extreme conditional sampling regularly is coupled with copula theory to assess the dependence between flood-risk drivers such as precipitation or river discharge and storm surge. The approach involves many subjective choices, including techniques used identify events [block maxima peaks-over-threshold (POT)], whether account for fit of marginal distributions, time-lags considered two drivers. In this study, estimates potential compound at three sites along Texas Gulf Coast, where...

Abstract Flood risk assessments commonly use event‐based approaches to reduce the number of scenarios required be run through computationally intensive physical process models. Often return period response variable (e.g., a fluvial water level or overtopping discharge) generated by an event upstream/downstream set sea state variables) does not match that itself; limitation which can lead misspecification flood risk. We present transferable hybrid statistical‐hydraulic modeling framework for...

Miami-Dade County is vulnerable to flash, pluvial, fluvial, coastal and groundwater flooding due its low-elevation karst morphology. Despite considerable advances in understanding the impact of compound events by considering major flood drivers (precipitation, river discharge, surge), little known regarding severity hazards this region. This study links a multivariate statistical analysis with coupled physically-based 2D hydraulic model estimate hazard Arch Creek Basin located North Miami. A...

The extraction of individual events from continuous time series is a common challenge in many extreme value studies. In the field environmental science, various methods and algorithms for event identification (de-clustering) have been applied past. distinctive features events, such as their temporal evolutions, durations, inter-arrival times, vary significantly one location to another making it difficult identify independent series. this study, we propose new automated approach detect...

Abstract. In coastal regions, compound flooding can arise from a combination of different drivers, such as storm surges, high tides, excess river discharge, and rainfall. Compound flood potential is often assessed by quantifying the dependence joint probabilities drivers using multivariate models. However, most these studies assume that all extreme events originate single population. This assumption may not be valid for regions where generation processes, e.g., tropical cyclones (TCs)...

Abstract In flood risk analysis, limitations in the multivariate statistical models adopted to model hydraulic load have restricted probability of a defense suffering structural failure be expressed conditionally on single loading variable. This is an issue at coastal level where multiple loadings act defenses with exact combination dictating their probabilities. Recently, methodology containing flexibility robustly capture dependence structure between individual was used derive extreme...

The extraction of individual events from continuous time series is a common challenge in many extreme value studies. In the field environmental science, various methods and algorithms for event identification (de-clustering) have been applied past. distinctive features events, such as their temporal evolutions, durations, inter-arrival times, vary significantly one location to another making it difficult identify independent series. this study, we propose new automated approach detect storm...

When different flooding drivers co-occur, they can cause compound floods. Despite the potential impact of flooding, few studies have projected how joint probability may change. Furthermore, existing projections are based on only 5 to 6 climate model simulations because such as storm surges and river run-off need be simulated offline using computationally expensive hydrodynamic hydrological models. Here, we use a large ensemble from Coupled Model Intercomparison Project project changes in...

Abstract. In coastal regions, compound flooding can arise from a combination of different drivers such as storm surges, high tides, excess river discharge, and rainfall. Compound flood potential is often assessed by quantifying the dependence joint probabilities using multivariate models. However, most these studies assume that all extreme events originate single population. This assumption may not be valid for regions where generation processes, e.g., tropical cyclones (TCs) extratropical...

Abstract In coastal regions, compound flooding, driven by multiple flood hazard sources, can cause greater damage than when the drivers occur in isolation. This study focuses on flooding from extreme precipitation and storm surge China’s Qiantang Estuary. We quantify potential of measuring bivariate joint statistical dependence return period (JRP). find a significant positive between two considered, as indicated Kendall’s rank correlation coefficients. Compound events frequently, with an...