Practitioners responsible for the design of urban stormwater management practices rely heavily on estimates of total impervious area (TIA) in a watershed. However, the most important parameter in determining actual urban runoff is "effective" impervious area (EIA), or the portion of TIA that is hydraulically connected to the storm sewer system. Knowledge of EIA is critical in rainfall-runoff modeling. The incorrect use of TIA instead of EIA in urban hydrologic modeling leads to an overestimation of runoff volumes and rates, and the best method for quantifying EIA in urban watersheds is the analysis of rainfall-runoff data sets, because it is based on observed data. In this study, the rainfall-runoff data analysis method was improved to decrease the uncertainty of EIA estimates. The improved method is based on successive weighted least square regression analysis. This method was applied to 9 urban watersheds with different sizes and characteristics in the Capitol Region Watershed District (CRWD), Minnesota. A procedure in ArcGIS was developed and applied to the study sites to un-shade the impervious surfaces that have been obscured by tree canopy. After modifying land cover layers, TIA was calculated in the watersheds of study in order to determine the ratio of "EIA/TIA". The results were used to show the importance of EIA in urban runoff modeling and evaluate the potential and the limitations of the proposed method. The method provides a better understanding of the runoff generation mechanisms in urban watersheds, reduces the uncertainty of EIA estimates and produces more accurate results that can be used to verify other EIA estimation techniques (e.g. GIS methods).