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Compound flooding, caused by the sequence/co-occurrence of flood drivers (i.e. river discharge and elevated sea level ) can lead to devastating consequences for society. Weak and insufficient progress toward sustainable development and disaster risk reduction are likely to exacerbate the catastrophic impacts of these events on vulnerable communities. For this reason, it is indispensable to develop new perspectives on evaluating compound flooding dependence and communicating the associated risks to meet UN Sustainable Development Goals (SDGs) related to climate action, sustainable cities, and sustainable coastal communities. An indispensable first step for studies examining the dependence between these bivariate extremes is plotting the data in the variable space, i.e., visualizing a scatterplot, where each axis represents a variable of interest, then computing a form of correlation between them. This paper introduces the Angles method, based on Euclidean geometry of the so-called “subject space,” for visualizing the dependence structure of compound flooding drivers. Here, we evaluate, for the first time, the utility of this geometric space in computing and visualizing the dependence structure of compound flooding drivers. To assess the effectiveness of this method as a risk communication tool, we conducted a survey with a diverse group of end-users, including academic and non-academic respondents. The survey results provide insights into the perceptions of applicability of the Angles method and highlight its potential as an intuitive alternative to scatterplots in depicting the evolution of dependence in the non-stationary environment. This study emphasizes the importance of innovative visualization techniques in bridging the gap between scientific insights and practical applications, supporting more effective compound flood hazard communication in a warming climate. 

Abstract. Compound flooding, caused by the sequence and/or co-occurrence of flood drivers (i.e., river discharge and elevated sea level), can lead to devastating consequences for society. Weak and insufficient progress toward sustainable development and disaster risk reduction is likely to exacerbate the catastrophic impacts of these events on vulnerable communities. For this reason, it is indispensable to develop new perspectives on evaluating compound-flooding dependence and communicating the associated hazards to meet UN Sustainable Development Goals (SDGs) related to climate action, sustainable cities, and sustainable coastal communities. The first step in examining bivariate dependence is to plot the data in the variable space, i.e., visualizing a scatterplot, where each axis represents a variable of interest, and then computing a form of correlation between them. This paper introduces the Angles method, based on Euclidean geometry of the so-called “subject space”, as a complementary visualization approach specifically designed for communicating the dependence structure of compound-flooding drivers to diverse end-users. Here, we evaluate, for the first time, the utility of this geometric space in computing and visualizing the dependence structure of compound-flooding drivers. To assess the effectiveness of this method as a hazard communication tool, we conducted a survey with a diverse group of end-users, including academic and non-academic respondents. The survey results provide insights into the perceptions regarding the applicability of the Angles method and highlight its potential as an intuitive alternative to scatterplots in depicting the evolution of dependence in the non-stationary environment. This study emphasizes the importance of innovative visualization techniques in bridging the gap between scientific insights and practical applications, supporting more effective compound flood hazard communication.