Despite recent advances in sensors, hydro-meteorological data remain scarce in urban watersheds. In the current, reactive approach to stormwater management, whether or not an urban flood event is documented, as well as where and how it actually occurred, is highly dependent on the level of monitoring. Even though there are many methods for observing flooding extent and predicting flooding vulnerability, issues with data availability and accuracy persist at the local level. Urban watersheds are spatially and temporally complex and flash floods, while of particular interest and importance to both hydrologists and communities, are hard to characterize, given that they are rare, spatially localized, short-lived, and often occur in locations without formal monitoring. On the other hand, identifying vulnerable areas in a large city using hydraulic/hydrological modeling would be very difficult, either because models have parameters that need to be calibrated against mostly non-existent data (in the case of conceptual models), or else we do not know all of the actual physical processes at work, or how to quantify them (in the case of physically-based models). Community-based monitoring activities can support the characterization of urban watersheds, as well as stormwater management, because they provide valuable spatial and temporal knowledge about the behavior of water flow and other related issues at a local level. An urban watershed study was conducted to demonstrate the value of community-based observations for understanding and characterizing urban pluvial flash flooding, by addressing the following questions: (i) How can communities feasibly monitor their local watershed using low-cost, straightforward approaches? (ii) How can local knowledge help us to better define and characterize urban pluvial flooding vulnerability? (iii) Are community-based data reliable and meaningful to urban watershed management and the decision-making process? To pursue these questions, participatory research was applied in a low-resourced community in the City of Paternò, in Sicily, Italy. We collected as unbiased as possible information about flash flooding events through 300 surveys. The locally-gathered data were compared to the results of advanced hydrodynamic models on smaller scales.