Statistical evaluation on hydrologic performance of bioretention design parameters under different rainfall conditions

Abstract

Effectiveness of a bioretention cell (BC) in mitigating stormwater peak flow load to an urban drainage system is highly dependent on the design configuration and retrofitting scale. The selection of appropriate BC design parameters has always been critical to achieving its maximum benefits. The BC modeling in the stormwater management model (SWMM) relies on numerous design parameters (in total of 18) with wide selection ranges, making parameter selection challenging. This study investigated the effect of hydrologic dynamics of BC design parameters under different rainfall conditions (i.e., intensity, duration, time-to-peak) on surface infiltration, surface outflow, and storage. Firstly, the seven influential BC design parameters (i.e., conductivity, berm height, vegetation volume, suction head, porosity, wilting point, and soil thickness) were selected based on one-factor-at-a-time (OAT) method, and 1000 random samples of each parameter were generated across the factor space by following respective uniform distributions. The simulations were performed with a python wrapper of SWMM (PySWMM) that used random samples for one parameter while leaving the others constant each time. In general, the statistical results of each parameter represent a significant variation in the volume distribution under various design rainfall conditions. Comparatively, the parameters of conductivity, berm height, and vegetation volume are categorized as the most influential compared to other BC design parameters for surface infiltration, storage, and surface outflow, respectively.