Unit-scale- and catchment-scale-based sensitivity analysis of bioretention cell for urban stormwater system management

Abstract

An improved understanding of bioretention cell (BC) design configuration at both the unit scale and catchment scale is necessary for critical insight into dynamical behaviors of design parameters, which resultantly guides and improves the effectiveness and efficiency of a BC. A comprehensive sensitivity analysis (SA) of BC design parameters was conducted in this study by using the Stormwater Management Model (SWMM) which is globally used for BC's modeling. The preliminary screening of various design parameters is conducted by the one-factor-at-a-time (OAT) SA method and the key influential parameters (i.e., conductivity, berm height, vegetation volume, suction head, porosity, wilting point, and soil thickness) are selected for further SA. To this end, 1,000 random uniformly distributed samples of each sensitive design parameter are simulated by a Python wrapper of SWMM (PySWMM) under different design storms at the unit scale and catchment scale, respectively. Unit-scale SA results found unique characteristics of each design parameter under different storm scenarios, and their behaviors toward different model responses dynamically change within their factor spaces. Catchment-scale SA results conclude vegetation and soil layers design parameters have significant impacts on controlling stormwater at the catchment scale, and optimal selection of design parameters of vegetation (type, density, and height) and soil (type, layer thickness, and void ratio) is necessary for significantly improving the effectiveness of the BC at the catchment scale.