Surface infiltration is a common method of reducing weather overflows from sanitary and stormwater systems. However, under- or overestimating contributing area to a stormwater control measure (SCM) can lead to suboptimal performance. Permeable pavement is a common stormwater control measure (SCM) to reduce peak flows in urban hydraulic conveyance systems. In urban environs, road and parking surfaces are often shallow and littered with channelized flowpaths (10mm - 30 mm in depth) as a result of microtopographic variance. Modeling efforts do not commonly account for the impact of microtopographic irregularities in the area contributing to a permeable pavement (PP) SCM itself. The increased availability of LIDAR equipment, drones, mapping services tools, and the drop in cost of LIDAR equipment has opened up opportunities to incorporate the data in both modeling and design aspects of Low Impact Development / Green Infrastructure (LID/GI) SCMs.
Two experiments were conducted on a parking lot in Cincinnati, Ohio, to estimate the impact of topographic resolution on catchment delineation and to identify evidence of microtopographic variation. The first experiment included sampling surface topography at multiple resolutions. The second experiment involved measuring SCM underdrain flow and comparing measured flow to modeled flow using subcatchments delineated from each resolution in the first experiment.
In the first experiment, a high-resolution LIDAR survey was performed using equipment capable of better than 61mm horizontal resolution and 3mm vertical resolution to produce rasterized maps ranging from coarse sampling (7620mm) to fine sampling (91mm) horizontal resolution of two interlocking concrete paver (ICP) cells that were 0.025 ha (Cell 82) and 0.015 ha (Cell 90). The calculated contributing area at Cell 82 decreased by 14% between fine and coarse horizontal sampling, whereas the contributing area increased by 1800% between fine and coarse sampling at Cell 90.
In the second experiment, field measurements of stormwater infiltration were obtained by sampling outflow through an underdrain pipe. The SCMs were compacted during installation to minimize groundwater infiltration, reducing the impact of external losses on volumetric calculations. An EPA-SWMM model was generated to represent surface infiltration as well as to model the ICP using the LID module. Simulations were generated for each of the topographic resolutions documented in the first experiment. Measured data were compared to modeled data for multiple events. All of the fine resolution simulations provided better agreement (using Nash-Sutcliffe efficiency) when compared to measured data than did the medium or coarse resolutions. Recommendations are provided to improve both modeling and SCM design.