We present an operational demonstration of Quantitative Flood Forecasting (QFF) during Tropical Storm Fay in 2008 in the Southern Appalachians. First, Quantitative Precipitation Forecast (QPF) datasets from the National Digital Forecast Database (NDFD) of the National Weather Service (NWS) were assessed through comparison with the Next Generation Multi-sensor QPE (Q2) products, and verification by a high-quality controlled rainfall dataset from the 1st phase of the Precipitation Measurement Mission (PMM) rain-gauge network in the Great Smoky Mountains (GSMRGN). Q2 along with NDFD QPF were utilized to force a physically-based distributed hydrological model to replicate operational flooding forecasting ensembles during Tropical Storm Fay over the Southern Appalachians over a four-day period in August 2008. Second, future GPM near real-time observations were simulated based on improved Q2+ data sets obtained by merging Q2 and observations from the GSMRGN optimally. The Q2+ data sets can be sampled at desired intervals to mimic GPM revisit periods. Finally, instantaneous GPM products were integrated with standard operational QPE estimates to drive the hydrology model and forecast flood response in three different watersheds. The results demonstrate that nudging nearly-instantaneous GPM data into operational QPE (Q2) could significantly improve the predictability of flash floods, specifically by extending flood warnings from 15 min to at least one hour lead time.