Until recently, the development of a global geography of floods was challenged by the fragmentation and heterogeneity of in situ data and the high costs of processing large amounts of remote sensing data. Such geography would facilitate the exploration of large-scale drivers of flood extent and timing including wide latitudinal, climate, and topographic effects. Here we used a monthly dataset spanning 30 years (Global Surface Water Extent) to develop a worldwide geographical characterization of slow floods (1-degree grid), weighting the relative contribution of seasonal, interannual, and long-term fluctuations on overall variability, and quantifying precipitation-flooding delays where seasonality dominated. We explored the dominance of different flooding timings across five Köppen-Geiger main climates and seven topography classes derived from modeled water table depths (i.e., hydro-topography) to contribute top-down insight about the outstanding, cross-regional flooding patterns and their likely large-scale drivers. Our results showed that, globally, the mean extent of floods averaged 0.48% of the global land area, predominantly associated with hydro-topography (>2x more extensive in flatter landscapes). Climate drove flood timings, with predictable, seasonally-dominated fluctuations in cold regions, interannual and mixed patterns in temperate climates, and more irregular (higher variability) and unpredictable (less seasonal) patterns in arid regions. Net gains of flooded area dominated temporal variability in 9% of the cells including boreal clusters likely affected by warming trends. We propose that this new geographical perspective of floods can aid different avenues of hydrological research in the upscaling and extrapolation of field studies and the parsimonious representation of floods in hydroclimatic models.