Developing Fine-scale Urban Drainage Models Using Remote Sensing and GIS Techniques

Within a wide range of best management practices (BMPs) for stormwater management in urban areas, there has been an increasing interest in source control measures in recent years. Source controls such as Low Impact Development (LID) techniques are also potentially attractive as retrofit options for areas that lack available land for stormwater management ponds to be implemented, but contribute to degradation of receiving water bodies. Development and running of hydrologic and hydraulic models are required to estimate the potential of LIDs to provide increased control of both quantity and quality of urban runoff. Traditional lumped models used in drainage system design and sizing of end-of-pipe controls may not be appropriate for modelling LIDs, which are typically distributed and small in size relative to catchment areas. Hence, fine-scale urban drainage models may be required to accurately estimate the benefit that LIDs may provide, requiring detailed representation of developed drainage areas. While detailed data required for the development of fine-scale models may be available for large municipalities in Canada, smaller communities typically lack such information and may benefit from using more broadly available remote sensed data. Satellite remote sensing has been demonstrated as a viable approach for acquiring topographic information to serve urban drainage modelling in a large spatial extent. Classification and extraction of land cover information are of particular importance to the development of a fine-scale hydrologic model in a complex urban environment. Thus, WorldView-2 satellite imagery is utilized in this study to extract land cover information. We present the use of remotely sensed data for detailed land cover classification, and demonstrate how the extracted information is used to construct homogeneous-area hydrologic models with the USEPA storm water management model (SWMM). The expected results of this approach pave the way for evaluating LID retrofit options and benefits accurately in situations where detailed drainage area information is not available.