Building resiliency to climate change uncertainty through bioretention design modifications

Abstract

Climate stationarity is a traditional assumption in the design of the urban drainage network, including green infrastructure practices such as bioretention cells. Predicted deviations from historic climate trends associated with global climate change introduce uncertainty in the ability of these systems to maintain service levels in the future. Climate change projections are made using output from coarse-scale general circulation models (GCMs), which can then be downscaled using regional climate models (RCMs) to provide predictions at a finer spatial resolution. However, all models contain sources of error and uncertainty, and predicted changes in future climate can be contradictory between models, requiring an approach that considers multiple projections. The performance of bioretention cells were modeled using USEPA's Storm Water Management Model (SWMM) to determine how design modifications could add resilience to these systems under future climate conditions projected for Knoxville, Tennessee, USA. Ten downscaled climate projections were acquired from the North American Coordinated Regional Downscaling Experiment program, and model bias was corrected using Kernel Density Distribution Mapping (KDDM). Bias-corrected climate projections were used to assess bioretention hydrologic function in future climate conditions. Several scenarios were evaluated using a probabilistic approach to determine the confidence with which design modifications could be implemented to maintain historic performance for both new and existing (retrofitted) bioretention cells. The largest deviations from current design (i.e., concurrently increasing ponding depths, thickness of media layer, media conductivity rates, and bioretention surface areas by 307%, 200%, 200%, and 300%, respectively, beyond current standards) resulted in the greatest improvements on historic performance with respect to annual volumes of infiltration and surface overflow, with all ten future climate scenarios across various soil types yielding increased infiltration and decreased surface overflow compared to historic conditions. However, lower performance was observed for more conservative design modifications; on average, between 13-82% and 77-100% of models fell below historic annual volumes of infiltration and surface overflow, respectively, when ponding zone depth, media layer thickness, and media conductivity were increased alone. Findings demonstrate that increasing bioretention surface area relative to the contributing catchment provides the greatest overall return on historic performance under future climate conditions and should be prioritized in locations with low in situ soil drainage rates. This study highlights the importance of considering local site conditions and management objectives when incorporating resiliency to climate change uncertainty into bioretention designs.

Keywords: Bioretention; Climate change; Hydrology; Resiliency; SWMM; Water balance.