Assessing the extent and impact of past extreme weather events within cities can help identify vulnerabilities, map potential solutions, and prevent future calamities. Modern urban environments are particularly vulnerable to hydrological extremes due to high population densities, expansive impermeable surfaces, more intense precipitation extremes, and infrastructure designed for a now obsolete climate. Intense rainfall in urban environments can lead to impacts ranging from nuisance flooding to overloading of sewage and drainage systems to neighborhood inundation. In the flood-prone city of Chicago, storm waters are contained in a network of tunnels and reservoirs until treated and released to the waterways. Management decisions for a 600 km^2 metropolitan area are made based on precipitation data collected at just 9 gauge sites. Here, we combine high-resolution radar-derived precipitation data with urban-scale hydrological models to improve our understanding of water flow, advance stormwater management practices, and potentially mitigate flood risks. Proximity of the NEXRAD system to Chicago allows us to improve the spatial resolution of rainfall estimates to 500m, which will be used to produce neighborhood-scale rainfall hindcasts. Different dual-polarimetric radar-rainfall retrieval methods, e.g., rainfall from reflectivity, attenuation, specific differential phase, and differential reflectivity will be examined to determine the most accurate representation of rainfall estimates. This suite of rainfall estimates will be used to derive catchment-level precipitation, and serve as input in a coupled hydrological-hydraulic MetroFlow model. To verify the utility of our radar precipitation data, we examine an April 2013 event that delivered a record-breaking 7 inches of rain in 2 days in some areas. We compare our highly-resolved precipitation-driven hydrological model predictions with those made using the 9 gauge stations. This research is conducted under the premise that hydrological extremes are expected to be exacerbated by climate change. Understanding drivers of urban flooding using high-resolution precipitation data and models can be used to improve resiliency-focused infrastructure design in Chicago neighborhoods.