Their model of an Italian urban catchment was calibrated using seven events from the existing conditions, and their calibration of green infrastructure performance was based on laboratory studies. Palla and Gnecco argued that an effective impervious area reduction larger than 5% is required to obtain noticeable hydrologic benefits from a combination of green roofs and permeable pavements. used data from individual events and existing conditions to calibrate their SWMM model in a study which showed 10–12% reductions in runoff from a semiarid watershed and hypothetical rainwater harvesting program. Their model was calibrated with data from six events using existing conditions only (no green infrastructure). showed that the combination of several green technologies led to changes in the runoff regime in a 12.3 ha medium-density residential area in Finland however, these practices were not able to fully restore predevelopment hydrological conditions. Previous studies using SWMM to examine the catchment-scale effects of green infrastructure have lacked robust calibration and validation using real data. SWMM also allows for a rainfall time step smaller than an hour, which represents an advantage over other green infrastructure computational tools, for example, RECARGA. The current SWMM version has the ability to simulate the hydrology of complex urban environments and considers the effect of various types of green infrastructure (i.e., bioretention cells, rain gardens, rain barrels, permeable pavement, rooftop disconnection, and green roofs) distributed across a catchment. A handful of recent studies have examined the catchment-scale effects of green infrastructure using the Storm Water Management Model (SWMM). Numerical modeling approaches remain the most widely used method of predicting the effects of green infrastructure, and modeling approaches are particularly useful to evaluate “what if” scenarios. When green infrastructure is retrofit into existing developments, the few catchment-scale studies have shown mixed results, with one study reporting large reductions in peak and total stormflows, another study reporting very small effects, detectible only with complex statistical analysis, and a third study still in its early stages. Catchment-scale studies of new development have found greater control of storm water runoff when green infrastructure is employed than when traditional, centralized storm water control measures are used. Although the effectiveness of storm water management practices has been assessed for different climates and designs, there is a limited knowledge base for how these solutions impact, separately or jointly, catchment-scale hydrology. Green infrastructure is designed to mitigate storm water impacts, and its success at doing so has been reported in multiple studies. Parameter and predictive uncertainties were inspected by implementing a Bayesian statistical approach. Discharges with a 0.5, 1, 2, and 5 year return period were reduced by an average of 29%. The flow duration curve shifted downward for the green infrastructure scenario. The hydrologic performance of green infrastructure was evaluated by comparing the flow duration curve for pretreatment and treatment outfall flow scenarios. For the study catchment, we observed a treatment effect with increases of 1.4% in evaporation, 7.6% in infiltration, and a 9.0% reduction in surface runoff. The calibrated model was used to quantify annual water budget alterations and discharge frequency over a 6 year simulation period. The Stormwater Management Model was calibrated and validated to predict the hydrologic response of green infrastructure. Data consisted of rainfall and outfall flow records for a wide range of storm events, including pretreatment and treatment periods. Green infrastructure included the following spatially distributed devices: 16 street-side bioretention cells, 7 rain gardens, and 37 rain barrels. In this study, we evaluated the cumulative hydrologic performance of green infrastructure in a residential area of the city of Parma, Ohio, draining to a tributary of the Cuyahoga River.
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