A Flood Risk Framework Capturing the Seasonality of and Dependence Between Rainfall and Sea Levels—An Application to Ho Chi Minh City, Vietnam

State-of-the-art flood hazard maps in coastal cities are often obtained from simulating coastal or pluvial events separately. This method does not account for the seasonality of flood drivers and their mutual dependence. In this article, we include the impact of these two factors in a computationally efficient probabilistic framework for...

A Copula-Based Bayesian Network for Modeling Compound Flood Hazard from Riverine and Coastal Interactions at the Catchment Scale: An Application to the Houston Ship Channel, Texas

Traditional flood hazard analyses often rely on univariate probability distributions; however, in many coastal catchments, flooding is the result of complex hydrodynamic interactions between multiple drivers. For example, synoptic meteorological conditions can produce considerable rainfall-runoff, while also generating wind-driven elevated sea...

Dependence between high sea-level and high river discharge increases flood hazard in global deltas and estuaries

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,...

Characterizing flood hazard at two spatial scales with the use of stochastic models: An application to the contiguous United States of America and the Houston Ship Channel

Flooding is the most common and one of the most damaging natural hazards globally. It has severe societal, economic and environmental consequences. Damages from floods are expected to worsen with changing climate and increasing population andwealthworldwide. Within the last decades, advances in computational power and increases in the number of...