  Cities increasingly face flood risk primarily due to extensive changes of the
natural land cover to built-up areas with impervious surfaces. In urban areas,
flood impacts come mainly from road interruption. This paper proposes an urban
flood risk map from hydrological and mobility data, considering the megacity of
S\~ao Paulo, Brazil, as a case study. We estimate the flood susceptibility
through the Height Above the Nearest Drainage algorithm; and the potential
impact through the exposure and vulnerability components. We aggregate all
variables into a regular grid and then classify the cells of each component
into three classes: Moderate, High, and Very High. All components, except the
flood susceptibility, have few cells in the Very High class. The flood
susceptibility component reflects the presence of watercourses, and it has a
strong influence on the location of those cells classified as Very High.
