Janke, BenGulliver, John S.Wilson, Bruce N.2011-08-022011-08-022011-07https://hdl.handle.net/11299/109971Practitioners responsible for the design and implementation of stormwater management practices rely heavily on estimates of impervious area in a watershed. However, the most important parameter in determining actual urban runoff is the ‘effective’ impervious area (EIA), or the portion of total impervious area that is directly connected to the storm sewer system. EIA, which is often considerably less than total impervious area and can vary with rainfall depth and intensity, is likely not determined with sufficient accuracy in current practice. A more accurate determination of EIA in a watershed would benefit a wide range of organizations involved in the design of stormwater management, pollution prevention, and transportation structures. This study investigated two existing methods of estimating EIA in a watershed: (1) analysis of large rainfall-runoff data sets using the method of Boyd et al. (1994), and (2) overlay analysis of spatial (GIS) data, including land cover, elevation, and stormwater infrastructure, using the method of Han and Burian (2009). The latter method provides an estimate of connected pavement, but requires the user to input the value of connected rooftop to determine the actual EIA value, which is the sum of these two quantities. The two methods were applied to two urban catchments within the Capitol Region Watershed in St. Paul, MN; one was a small (42-ac), relatively uniform residential neighborhood, and the other was a large (3400-ac), highly-urbanized catchment with a variety of land uses present. The results were used to evaluate the potential of each method and make recommendations for future studies. In summary, the data analysis technique (Boyd et al., 1994) has the advantage of being quick and relatively simple to implement, as it did not require familiarity with specialized software tools (e.g. ArcGIS) and could be completed with any spreadsheet program with graphing capabilities (e.g. Excel). The EIA estimates from the data analysis are the most accurate, but the technique is unable to determine where in the watershed the EIA is located, and cannot be used if runoff discharge and local precipitation data is unavailable. By contrast, the GIS method (Han and Burian, 2009) has the advantage of being applicable to un-gauged watersheds, and also provides the location of EIA in the watershed. This latter feature makes it particularly attractive for honing the development and placement of BMP’s in a watershed. Unfortunately, the accuracy of the GIS method is completely dependent on the ability to faithfully represent the amount of roof connection in a watershed, a process that can add significant time and expense to the EIA estimate.Future work should be focused primarily on two general areas: (1) improving the GIS-based estimation technique, and (2) expanding the application of both techniques to additional sub-watersheds, with particular emphasis on newer development and on catchments with more homogenous land uses. The GIS method could be improved considerably by developing techniques to improve roof connectivity estimates, e.g. through the use of land use-specific site surveys or through some novel partitioning scheme based on age or type of rooftop. An improved method for handling canopy shading of impervious surfaces than that used herein could also be investigated. Insight on both of these areas of improvement could be supplied by application of both the data analysis and the GIS-based techniques to additional watersheds. Furthermore, additional analyses could potentially allow EIA values to be correlated to land cover characteristics such as roof type, canopy shading, age of construction, lane-miles of road, BMP presence, etc. or even to rainfall characteristics such as intensity, duration, or antecedent rainfall depth. This type of generalized information would be valuable to practitioners in applications such as stormwater management, transportation design, or water quality protection.en-USReport