Building resiliency to climate change uncertainty through bioretention design modifications

Area of Science:

• Environmental Engineering
• Urban Hydrology
• Climate Change Adaptation

Background:

• Traditional urban drainage design assumes climate stationarity, which is challenged by global climate change.
• Green infrastructure, like bioretention cells, may not maintain service levels under future climate conditions.
• Climate change projections from General Circulation Models (GCMs) require downscaling by Regional Climate Models (RCMs), introducing model uncertainty.

Purpose of the Study:

• To model bioretention cell performance using future climate projections.
• To determine design modifications for enhancing bioretention resilience to climate change.
• To assess the effectiveness of these modifications for new and retrofitted systems.

Main Methods:

• Utilized the Storm Water Management Model (SWMM) for bioretention performance simulation.
• Acquired ten bias-corrected climate projections from the North American Coordinated Regional Downscaling Experiment (NA-CORDEX) using Kernel Density Distribution Mapping (KDDM).
• Evaluated multiple design modification scenarios using a probabilistic approach.

Main Results:

• Significant design modifications (increased ponding depths, media thickness, conductivity, and surface area) greatly improved historic performance metrics.
• All ten future climate scenarios showed increased infiltration and decreased surface overflow with substantial design changes.
• Conservative modifications alone yielded lower performance, with some models falling below historic infiltration and overflow volumes.

Conclusions:

• Increasing bioretention surface area relative to the catchment is the most effective strategy for maintaining historic performance under future climate conditions.
• Prioritize larger surface areas in locations with poor in situ soil drainage.
• Local site conditions and management goals are crucial for designing resilient bioretention systems against climate change uncertainty.