title: Catchment-Scale Rain Garden Effectiveness and its Spatiotemporal Factors: A Case Study in Columbia, Maryland
Creators: name: Daniels, Benjamin
Publisher: name: Maryland Shared Open Access Repository
Year: 2024
Subjects: subject: green infrastructure
subject: low-impact development
subject: rain gardens
subject: stormwater management
subject: SWMM
subject: urban hydrology

description: Rain gardens (RGs) are vegetated depressional areas that collect and infiltrate runoff, and are increasingly used to manage stormwater from detached houses in residential areas, although their catchment-scale effects are not well understood. I investigate the catchment-scale hydrologic effectiveness of residential RGs for reducing stormflow in suburban catchments, and how it varies across space and time. I developed a hydrologic model of a 3.1 km2 suburban catchment in Columbia, MD, USA, to simulate the effects of various residential RG implementation scenarios on event hydrology. I addressed the following research questions: (1) What is the capacity of residential RGs to mitigate event runoff in an intermediate-sized, suburban catchment? (2) What are the effects of spatial distribution of RGs on event runoff? and (3) What are the effects of rainfall characteristics and antecedent moisture condition (AMC) on the catchment-scale effectiveness of residential RGs for event runoff control?Using the Storm Water Management Model (SWMM), I simulated implementation of RGs at 25%, 50%, 75%, and 100% of detached houses in the study catchment to determine the effects on peak flow, runoff volume, and lag time over a 3-year period. I also simulated three contrasting pairs of spatial scenarios: upstream vs. downstream, clustered vs. dispersed, and near-stream vs. far-stream RG implementation scenarios. Finally, I analyzed the influence of rainfall characteristics and AMC on the effectiveness of RGs for event runoff control in the study catchment. I found that, on average, treating 100% of residential rooftops with RGs reduced peak flows by 14.5%, reduced runoff volumes by 11.7%, and increased lag times by 2.9% for the 211 rainfall events in the simulation period. The results of the spatial scenario simulations indicated that the spatial distribution of RGs had a small but statistically significant effect (p&lt;0.01) on event runoff. On average, peak flows and runoff volumes in the clustered scenario were 2.4% less and 0.2% less, respectively, than those of the dispersed scenario. Peaks flows and runoff volumes in the upstream scenario were 2.5% less and 0.2% more, respectively, than those of the downstream scenario, on average. Peak flows and runoff volumes for the near-stream scenario were 1.1% more and 0.3% more, respectively, than those of the far-stream scenario, on average. Mean lag times for the spatial scenarios were all within 1.0% of those of their partner scenarios. Finally, I found that the cumulative effectiveness of RGs for reducing peak flows and increasing lag times decreased significantly with increasing rainfall depth, intensity, and duration. Runoff volume reduction was negatively correlated with rainfall depths above 10 mm and with rainfall intensities above 10 mm/hr, but not with storm duration. Catchment-scale RG performance was not correlated with two proxies for catchment AMC (i.e., 7-day antecedent rainfall and pre-event discharge). This research demonstrates that residential RGs can significantly improve the runoff response of suburban catchments, and that their effectiveness varies depending on their spatial distribution and on rainfall characteristics.