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. Conventional flood risk methods typically focus on estimation at a singlelocation, which can be inadequate for civil infrastructure systems such asroad or railway infrastructure. This is because rainfall extremes arespatially dependent; to understand overall system risk, it isnecessary to assess the interconnected elements of the system jointly. Forexample, when designing evacuation routes it is necessary to understand therisk of one part of the system failing given that another region is floodedor exceeds the level at which evacuation becomes necessary. Similarly,failure of any single part of a road section (e.g., a flooded rivercrossing) may lead to the wider system's failure (i.e., the entire roadbecomes inoperable). This study demonstrates a spatially dependentintensity–duration–frequency (IDF) framework that can be used to estimate floodrisk across multiple catchments, accounting for dependence both in space andacross different critical storm durations. The framework is demonstrated viaa case study of a highway upgrade comprising five river crossings. Theresults show substantial differences in conditional and unconditional designflow estimates, highlighting the importance of taking an integratedapproach. There is also a reduction in the estimated failure probability ofthe overall system compared with the case where each river crossing istreated independently. The results demonstrate the potential uses ofspatially dependent intensity–duration–frequency methods and suggest theneed for more conservative design estimates to take into account conditionalrisks.

Spatially dependent flood probabilities to support the design of civil infrastructure systems