When river and coastal floods coincide, their impacts are often worse than when they occur in isolation; such floods are examples of 'compound events'. To better understand the impacts of these compound events, we require an improved understanding of the dependence between coastal and river flooding on a global scale. Therefore, in this letter, we: provide the first assessment and mapping of the dependence between observed high sea-levels and high river discharge for deltas and estuaries around the globe; and demonstrate how this dependence may influence the joint probability of floods exceeding both the design discharge and design sea-level. The research was carried out by analysing the statistical dependence between observed sea-levels (and skew surge) from the GESLA-2 dataset, and river discharge using gauged data from the Global Runoff Data Centre, for 187 combinations of stations across the globe. Dependence was assessed using Kendall's rank correlation coefficient ( ) and copula models. We find significant dependence for skew surge conditional on annual maximum discharge at 22% of the stations studied, and for discharge conditional on annual maximum skew surge at 36% of the stations studied. Allowing a time-lag between the two variables up to 5 days, we find significant dependence for skew surge conditional on annual maximum discharge at 56% of stations, and for discharge conditional on annual maximum skew surge at 54% of stations. Using copula models, we show that the joint exceedance probability of events in which both the design discharge and design sea-level are exceeded can be several magnitudes higher when the dependence is considered, compared to when independence is assumed. We discuss several implications, showing that flood risk assessments in these regions should correctly account for these joint exceedance probabilities.

Abstract. The interaction between physical drivers from oceanographic, hydrological, and meteorological processes in coastal areas can result in compound flooding. Compound flood events, like Cyclone Idai and Hurricane Harvey, have revealed the devastating consequences of the co-occurrence of coastal and river floods. A number of studies have recently investigated the likelihood of compound flooding at the continental scale based on simulated variables of flood drivers, such as storm surge, precipitation, and river discharges. At the global scale, this has only been performed based on observations, thereby excluding a large extent of the global coastline. The purpose of this study is to fill this gap and identify regions with a high compound flooding potential from river discharge and storm surge extremes in river mouths globally. To do so, we use daily time series of river discharge and storm surge from state-of-the-art global models driven with consistent meteorological forcing from reanalysis datasets. We measure the compound flood potential by analysing both variables with respect to their timing, joint statistical dependence, and joint return period. Our analysis indicates many regions that deviate from statistical independence and could not be identified in previous global studies based on observations alone, such as Madagascar, northern Morocco, Vietnam, and Taiwan. We report possible causal mechanisms for the observed spatial patterns based on existing literature. Finally, we provide preliminary insights on the implications of the bivariate dependence behaviour on the flood hazard characterisation using Madagascar as a case study. Our global and local analyses show that the dependence structure between flood drivers can be complex and can significantly impact the joint probability of discharge and storm surge extremes. These emphasise the need to refine global flood risk assessments and emergency planning to account for these potential interactions.

Abstract. Coastal flood hazard and exposure are expected to increase over the course of the 21st century, leading to increased coastal flood risk. In order to limit the increase in future risk, or even reduce coastal flood risk, adaptation is necessary. Here, we present a framework to evaluate the future benefits and costs of structural protection measures at the global scale, which accounts for the influence of different flood risk drivers (namely sea-level rise, subsidence, and socioeconomic change). Globally, we find that the estimated expected annual damage (EAD) increases by a factor of 150 between 2010 and 2080 if we assume that no adaptation takes place. We find that 15 countries account for approximately 90 % of this increase. We then explore four different adaptation objectives and find that they all show high potential in cost-effectively reducing (future) coastal flood risk at the global scale. Attributing the total costs for optimal protection standards, we find that sea-level rise contributes the most to the total costs of adaptation. However, the other drivers also play an important role. The results of this study can be used to highlight potential savings through adaptation at the global scale.