AbstractAccounting for seasonal effects on rain garden performance can be challenging in colder regions. Changes in temperature cause changes in the viscosity of water, infiltration rates, and evapotranspiration rates. A variably saturated hydrologic model (HYDRUS-1D) was calibrated and validated using observed ponding depth and soil moisture data from two different storm events for a rain garden owned and operated by the Philadelphia Water Department (PWD). Warm and cold seasons were simulated with typical meteorological data and temperature-adjusted saturated hydraulic conductivity values. Design storm simulations confirmed that the rain garden is over-performing. By increasing the loading ratio (i.e., the ratio of drainage area to rain garden footprint) in the model, the maximum capacity of the rain garden was estimated to be 43% more than the design in the cold season, and 110% more than that in the warm season. If the maximum allowable ponding was raised to accommodate more water depth, the rain garden could have a maximum capacity 205% larger than the design while still meeting the PWD’s 24-h drain down requirement. This study demonstrates (1) how to develop a simple one-dimensional (1D) model that can reasonably account for seasonal effects on rain garden performance; and (2) the use of this model to quantify system capacity year-round and ultimately inform regulations and design.

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