Enhanced Bioretention Modeling at the Catchment-Scale: An Integrated DRAINMOD-Urban and SWMM Approach

Bioretention systems are increasingly being adopted in stormwater management as an effective measure to promote infiltration and restore more natural hydrology in urbanized watersheds. Given the significant financial investment in these practices, reliable bioretention models are necessary to predict the effectiveness of these practices prior to installation. One such model, DRAINMOD-Urban (DM-Urban), was recently developed to produce hydrographs with a high temporal resolution at the site-scale, showing substantial promise during initial testing. However, the dataset used for initial testing was limited, consisting of one bioretention area with minimal occasions of overflow. Additionally, DM-Urban is an input-heavy model and there is limited understanding as to which inputs require high accuracy in this context. To achieve a more robust analysis, DM-Urban was evaluated using two years of monitoring data from four bioretention cells in North Carolina. Results confirmed that DM-Urban can model the hydrographs and total volume of both bioretention drainage and overflow at a fine temporal scale under varying design configurations such as variable media depths, surface storage volumes, site conditions, and surface clogging (which increases overflow). Furthermore, to determine the most influential DM-Urban input parameters, a variance-based sensitivity analysis was employed to examine the impact of uncertainty of parameterization on uncalibrated model output. The analysis found that DM-Urban is sensitive to ten parameters, classified into three categories, with varying levels of sensitivity depending on the model output of interest. This highlights the importance of accurate parameterization in bioretention modeling and the need to account for parameter uncertainty in uncalibrated DM-Urban models. Finally, to advance watershed-scale scenario-testing of bioretention placement, DM-Urban (DMU), a site-scale bioretention model, was coupled with the Storm Water Management Model (SWMM) to enhance bioretention representation at the catchment scale. The coupled SWMM-DMU model showed substantial improvement in representing bioretention at the watershed scale in comparison to SWMM with its Low Impact Development (LID) module. These studies greatly contribute to enhancing the practice of bioretention cell modeling at the catchment scale to inform watershed restoration projects.