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Abstract. Miami-Dade County (south-east Florida) is among the most vulnerable regions to sea level rise in the United States, due to a variety of natural andhuman factors. The co-occurrence of multiple, often statistically dependent flooding drivers – termed compound events – typically exacerbatesimpacts compared with their isolated occurrence. Ignoring dependencies between the drivers will potentially lead to underestimation of flood riskand under-design of flood defence structures. In Miami-Dade County water control structures were designed assuming full dependence between rainfalland Ocean-side Water Level (O-sWL), a conservative assumption inducing large safety factors. Here, an analysis of the dependence between theprincipal flooding drivers over a range of lags at three locations across the county is carried out. A two-dimensional analysis of rainfall andO-sWL showed that the magnitude of the conservative assumption in the original design is highly sensitive to the regional sea level rise projectionconsidered. Finally, the vine copula and Heffernan and Tawn (2004) models are shown to outperform five standard higher-dimensional copulas incapturing the dependence between the principal drivers of compound flooding: rainfall, O-sWL, and groundwater level. The work represents a firststep towards the development of a new framework capable of capturing dependencies between different flood drivers that could potentially beincorporated into future Flood Protection Level of Service (FPLOS) assessments for coastal water control structures. 

The cooccurrence of coastal and riverine flooding leads to compound events with substantial impacts on people and property in low‐lying coastal areas. Climate change could increase the level of compound flood hazard through higher extreme sea levels and river flows. Here, a bivariate flood hazard assessment method is proposed to estimate compound coastal‐riverine frequency under current and future climate conditions. A copula‐based approach is used to estimate the joint return period (JRP) of compound floods by incorporating sea‐level rise (SLR) and changes in peak river flows into the marginal distributions of flood drivers. Specifically, the changes in JRP of compound major coastal‐riverine flooding defined based on simultaneous exceedances above major coastal and riverine thresholds, are explored by midcentury. Subsequently, the increase in the probability of occurrence of at least one compound major coastal‐riverine flooding for a given period of time is quantified. The proposed compound flood hazard assessment is conducted at 26 paired tidal‐riverine stations along the Contiguous United States coast with long‐term data and defined flood thresholds. We show that the northeast Atlantic and the western part of the Gulf coasts are experiencing the highest compound major coastal‐riverine flood probability under current conditions. However, future SLR scenarios show the highest frequency amplification along the southeast Atlantic coast. The impact of changes in peak river flows is found to be considerably less than that of SLR. Climate change impacts, especially SLR, may lead to more frequent compound events, which cannot be ignored for future adaptation responses in estuary regions.

 

Flood exposure is increasing in coastal communities due to rising sea levels. Understanding the effects of sea level rise (SLR) on frequency and consequences of coastal flooding and subsequent social and economic impacts is of utmost importance for policymakers to implement effective adaptation strategies. Effective strategies may consider impacts from cumulative losses from minor flooding as well as acute losses from major events. In the present study, a statistically coherent Mixture Normal‐Generalized Pareto Distribution model was developed, which reconciles the probabilistic characteristics of the upper tail as well as the bulk of the sea level data. The nonstationary sea level condition was incorporated in the mixture model using Quantile Regression method to characterize variable Generalized Pareto Distribution thresholds as a function of SLR. The performance validity of the mixture model was corroborated for 68 tidal stations along the Contiguous United States (CONUS) coast with long‐term observed data. The method was subsequently employed to assess existing and future coastal minor and major flood frequencies. The results indicate that the frequency of minor and major flooding will increase along all CONUS coastal regions in response to SLR. By the end of the century, under the “Intermediate” SLR scenario, major flooding is anticipated to occur with return period less than a year throughout the coastal CONUS. However, these changes vary geographically and temporally. The mixture model was reconciled with the property exposure curve to characterize how SLR might influence Average Annual Exposure to coastal flooding in 20 major CONUS coastal cities.