Inferring the mechanisms causing river flooding is key to understanding past, present, and future flood risk. However, a quantitative spatially distributed overview of the mechanisms that drive flooding across Europe is currently unavailable. In addition, studies that classify catchments according to their flood-driving mechanisms often identify a single mechanism per location, although multiple mechanisms typically contribute to flood risk. We introduce a new method that uses seasonality statistics to estimate the relative importance of extreme precipitation, soil moisture excess, and snowmelt as flood drivers. Applying this method to a European data set of maximum annual flow dates in several thousand catchments reveals that from 1960 to 2010 relatively few annual floods were caused by annual rainfall peaks. Instead, most European floods were caused by snowmelt and by the concurrence of heavy precipitation with high antecedent soil moisture. For most catchments, the relative importance of these mechanisms has not substantially changed during the past five decades. Exposing the regional mechanisms underlying Europe's most costly natural hazard is a key first step in identifying the processes that require most attention in future flood research.

Fluvial landscapes are dissected by channels, and at their upstream termini are channel heads.Accurate reconstruction of the fluvial domain is fundamental to understanding runoff generation, storm hydrology, sediment transport, biogeochemical cycling, and landscape evolution. Many methods have been proposed for predicting channel head locations using topographic data, yet none have been tested against a robust field data set of mapped channel heads across multiple landscapes. In this study, four methods of channel head prediction were tested against field data from four sites with high-resolution DEMs: slopearea scaling relationships; two techniques based on landscape tangential curvature; and a new method presented here, which identifies the change from channel to hillslope topography along a profile using a transformed longitudinal coordinate system. Our method requires only two user-defined parameters, determined via independent statistical analysis. Slope-area plots are traditionally used to identify the fluvialhillslope transition, but we observe no clear relationship between this transition and field-mapped channel heads. Of the four methods assessed, one of the tangential curvature methods and our new method most accurately reproduce the measured channel heads in all four field sites (Feather River CA, Mid Bailey Run OH, Indian Creek OH, Piedmont VA), with mean errors of 211, 27, 5, and 224 m and 34, 3, 12, and 258 m, respectively. Negative values indicate channel heads located upslope of those mapped in the field. Importantly, these two independent methods produce mutually consistent estimates, providing two tests of channel head locations based on independent topographic signatures.

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Flooding is a major hazard to lives and infrastructure, but trends in flood hazard are poorly understood. The capacity of river channels to convey flood flows is typically assumed to be stationary, so changes in flood frequency are thought to be driven primarily by trends in streamflow. We have developed new methods for separately quantifying how trends in both streamflow and channel capacity have affected flood frequency at gauging sites across the United States Flood frequency was generally nonstationary, with increasing flood hazard at a statistically significant majority of sites. Changes in flood hazard driven by channel capacity were smaller, but more numerous, than those driven by streamflow. Our results demonstrate that accurately quantifying changes in flood hazard requires accounting separately for trends in both streamflow and channel capacity. They also show that channel capacity trends may have unforeseen consequences for flood management and for estimating flood insurance costs.