Long-term simulation of green infrastructure effects at a catchment-scale

The Watershed Hydrology Lab will be represented at the CUAHSI Biennial Symposium in July in West Virginia. Pedro Avellaneda and Laura Sugano have been awarded travel grants to present their research. Here’s Pedro’s abstract:

Long-term simulation of green infrastructure effects at a catchment-scale

Pedro M. Avellaneda1, Anne J. Jefferson2, Jennifer M. Grieser3

1 Department of Geology, Kent State University, 221 McGilvery Hall, Kent, OH, 44242, USA; Phone: 330-672-2680; email: pavellan@kent.edu
2 Department of Geology, Kent State University, 221 McGilvery Hall, Kent, OH, 44242, USA; Phone: 330-672-2746; email: ajeffer9@kent.edu
3 Cleveland Metroparks, 2277 W Ridgewood Dr, Parma, OH, 44134, USA; Phone: 440-253-2163; email: jmg2@clevelandmetroparks.com

ABSTRACT

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. Green infrastructure involved the following spatially distributed devices: 16 street side bioretentions, 7 rain gardens, and 37 rain barrels. The catchment has an area of 7.2 ha, in which 0.7% is occupied by green infrastructure and 40% is covered by impervious surfaces. Green infrastructure is expected to treat 72% of impervious areas. The engineered soils for the bioretentions and rain gardens consisted of sand (~72%), organic matter (5-28%), and clay (~10%). Data consisted of rainfall and outfall flow records for a wide range of storm events ?from 0.3 mm to 81.3 mm of measurable precipitation? including pre-treatment and treatment periods. The rainfall-runoff process was simulated for a 10 year period using the Stormwater Management Model (SWMM), a dynamic hydrology and hydraulic model that incorporates green infrastructure. Two scenarios were considered for the application of the SWMM model: pre-treatment, considering observed data before construction of green infrastructure; and treatment, considering observed data after installation of green infrastructure. The calibrated and validated SWMM model was used to evaluate ?using the same climate characteristics? the long-term hydrologic alteration due to the green infrastructure. A 0.8% increase in evaporation, a 12% increase in infiltration, a 1.6% drainage from green infrastructure, and a 14.4% reduction in surface runoff were produced. A simulated flow duration curve for the treatment scenario was compared to that of a pre-treatment scenario. The flow duration curve shifted downwards for the green infrastructure scenario, with a 30% decrease in the Q99, Q98, and Q95 percentiles. Parameter and predictive uncertainties were inspected by implementing a Bayesian statistical approach.