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  1. Free, publicly-accessible full text available April 1, 2023
  2. Abstract. The interaction between storm surge and concurrent precipitation is poorly understood in many coastal regions. This paper investigates the potential compound effects from these two flooding drivers along the coast of China for the first time by using the most comprehensive records of storm surge and precipitation. Statistically significant dependence between flooding drivers exists at the majority of locations that are analysed, but the strength of the correlation varies spatially and temporally and depending on how extreme events are defined. In general, we find higher dependence at the south-eastern tide gauges (TGs) (latitude < 30∘ N) compared to the northern TGs. Seasonal variations in the dependence are also evident. Overall there are more sites with significant dependence in the tropical cyclone (TC) season, especially in the summer. Accounting for past sea level rise further increases the dependence between flooding drivers, and future sea level rise will hence likely lead to an increase in the frequency of compound events. We also find notable differences in the meteorological patterns associated with events where both drivers are extreme versus events where only one driver is extreme. Events with both extreme drivers at south-eastern TG sites are caused by low-pressure systems with similar characteristics across locations, including high precipitable watermore »content (PWC) and strong winds that generate high storm surge. Based on historical disaster damages records of Hong Kong, events with both extreme drivers account for the vast majority of damages and casualties, compared to univariate flooding events, where only one flooding driver occurred. Given the large coastal population and low capacity of drainage systems in many Chinese urban coastal areas, these findings highlight the necessity to incorporate compound flooding and its potential changes in a warming climate into risk assessments, urban planning, and the design of coastal infrastructure and flood defences.« less
  3. Abstract. Flooding is of particular concern in low-lying coastal zones that are prone to flooding impacts from multiple drivers, such as oceanographic (storm surge and wave), fluvial (excessive river discharge), and/or pluvial (surface runoff). In this study, we analyse, for the first time, the compound flooding potential along the contiguous United States (CONUS) coastline from all flooding drivers, using observations and reanalysis data sets. We assess the overall dependence from observations by using Kendall's rank correlation coefficient (τ) and tail (extremal) dependence (χ). Geographically, we find the highest dependence between different drivers at locations in the Gulf of Mexico, southeastern, and southwestern coasts. Regarding different driver combinations, the highest dependence exists between surge–waves, followed by surge–precipitation, surge–discharge, waves–precipitation, and waves–discharge. We also perform a seasonal dependence analysis (tropical vs. extra-tropical season), where we find higher dependence between drivers during the tropical season along the Gulf and parts of the East Coast and stronger dependence during the extra-tropical season on the West Coast. Finally, we compare the dependence structure of different combinations of flooding drivers, using observations and reanalysis data, and use the Kullback–Leibler (KL) divergence to assess significance in the differences of the tail dependence structure. We find, for example, that models underestimate the tailmore »dependence between surge–discharge on the East and West coasts and overestimate tail dependence between surge–precipitation on the East Coast, while they underestimate it on the West Coast. The comprehensive analysis presented here provides new insights on where the compound flooding potential is relatively higher, which variable combinations are most likely to lead to compounding effects, duringwhich time of the year (tropical versus extra-tropical season) compoundflooding is more likely to occur, and how well reanalysis data capture thedependence structure between the different flooding drivers.« less
  4. Abstract. In coastal regions, floods can arise through a combination of multipledrivers, including direct surface run-off, river discharge, storm surge, andwaves. In this study, we analyse compound flood potential in Europe andenvirons caused by these four main flooding sources using state-of-the-artdatabases with coherent forcing (i.e. ERA5). First, we analyse thesensitivity of the compound flooding potential to several factors: (1)sampling method, (2) time window to select the concurrent event of theconditioned driver, (3) dependence metrics, and (4) wave-driven sea leveldefinition. We observe higher correlation coefficients using annual maximathan peaks over threshold. Regarding the other factors, our results showsimilar spatial distributions of the compound flooding potential. Second, thedependence between the pairs of drivers using the Kendall rank correlationcoefficient and the joint occurrence are synthesized for coherent patterns ofcompound flooding potential using a clustering technique. This quantitativemulti-driver assessment not only distinguishes where overall compound floodingpotential is the highest, but also discriminates which driver combinations aremore likely to contribute to compound flooding. We identify that hotspots ofcompound flooding potential are located along the southern coast of the NorthAtlantic Ocean and the northern coast of the Mediterranean Sea.
  5. 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 Floodmore »Protection Level of Service (FPLOS) assessments for coastal water control structures.« less