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Floods are a natural hazard that affect communities worldwide, but to date the vast majority of flood hazard research and mapping has been undertaken by wealthy developed nations. As populations and economies have grown across the developing world, so too has demand from governments, businesses, and NGOs for modeled flood hazard data in these data‐scarce regions. We identify six key challenges faced when developing a flood hazard model that can be applied globally and present a framework methodology that leverages recent cross‐disciplinary advances to tackle each challenge. The model produces return period flood hazard maps at ∼90 m resolution for the whole terrestrial land surface between 56°S and 60°N, and results are validated against high‐resolution government flood hazard data sets from the UK and Canada. The global model is shown to capture between two thirds and three quarters of the area determined to be at risk in the benchmark data without generating excessive false positive predictions. When aggregated to ∼1 km, mean absolute error in flooded fraction falls to ∼5%. The full complexity global model contains an automatically parameterized subgrid channel network, and comparison to both a simplified 2‐D only variant and an independently developed pan‐European model shows the explicit inclusion of channels to be a critical contributor to improved model performance. While careful processing of existing global terrain data sets enables reasonable model performance in urban areas, adoption of forthcoming next‐generation global terrain data sets will offer the best prospect for a step‐change improvement in model performance.

This work advances a unified approach to process-based hydrologic modeling to enable controlled and systematic evaluation of multiple model representations (hypotheses) of hydrologic processes and scaling behavior. Our approach, which we term the Structure for Unifying Multiple Modeling Alternatives (SUMMA), formulates a general set of conservation equations, providing the flexibility to experiment with different spatial representations, different flux parameterizations, different model parameter values, and different time stepping schemes. In this paper, we introduce the general approach used in SUMMA, detailing the spatial organization and model simplifications, and how different representations of multiple physical processes can be combined within a single modeling framework. We discuss how SUMMA can be used to systematically pursue the method of multiple working hypotheses in hydrology. In particular, we discuss how SUMMA can help tackle major hydrologic modeling challenges, including defining the appropriate complexity of a model, selecting among competing flux parameterizations, representing spatial variability across a hierarchy of scales, identifying potential improvements in computational efficiency and numerical accuracy as part of the numerical solver, and improving understanding of the various sources of model uncertainty.

[1] We conducted a detailed study of subsurface flow and water table response coupled with digital terrain analysis (DTA) of surface and subsurface features at the hillslope scale in Panola Mountain Research Watershed (PMRW), Georgia. Subsurface storm flow contributions of macropore and matrix flow in different sections along an artificial trench face were highly variable in terms of timing, peak flow, recession characteristics, and total flow volume. The trench flow characteristics showed linkages with the spatial tensiometer response defining water table development upslope. DTA of the ground surface did not capture the observed spatial patterns of trench flow or tensiometric response. However, bedrock surface topographic indices significantly improved the estimation of spatial variation of flow at the trench. Point-scale tensiometric data were also more highly correlated with the bedrock surface-based indices. These relationships were further assessed for temporal changes throughout a rainstorm. Linkages between the bedrock indices and the trench flow and spatial water table responses improved during the wetter periods of the rainstorm, when the hillslope became more hydrologically connected. Our results clearly demonstrate that in developing a conceptual framework for understanding the mechanisms of runoff generation, local bedrock topography may be highly significant at the hillslope scale in some catchments where the bedrock surface acts as a relatively impermeable boundary.