Planning & Management
397852 - Guiding green stormwater infrastructure planning through socio-ecological vulnerability: An integrated and spatially scalable optimization framework for prioritizing sites in urban areas
Wednesday, June 6
10:30 AM - 12:00 PM
Location: Greenway GH
Morgan Grove, Suite 350, 5523 Research Park Drive Baltimore, MD, 21228 – US Forest Service; Julie Cidell, 255 CAB, MC-150 605 E. Springfield Ave. Champaign, IL 61820 – University of Illinois at Urbana-Champaign; Arthur Schmidt, 2535a Hydrosystems Lab 205 N. Mathews Urbana Illinois 61801 – University of Illinois at Urbana-Champaign; Barbara Minsker, PO Box 750340 3101 Dyer Street, 203G Embrey Bldg. Dallas, TX 75275-0340 – Southern Methodist University
Green stormwater infrastructure (GSI) (e.g., rain gardens, bioswales, trees, etc.) is widely used for its potential to reduce storm water management problems (e.g., poor water quality and increased streamflow velocities and flood risk due to impervious surfaces) while also benefitting human and ecosystem health. Despite increasing attention to the implementation of GSI, current planning and design methodologies typically do not adequately integrate site-scale design decisions with catchment-scale impacts and fail to consider the significant environmental and social justice implications of GSI siting decisions. Planning decisions are often based on limited information about where different types of GSI will be most effective and the entire suite of socio-ecological benefits and risks associated with multiple hazards.
This study presents a spatially-scalable optimization framework that uses the vulnerability of socio-ecologic systems as drivers for prioritizing locations and types of GSI installations. The framework rapidly identifies areas with the greatest suitability for GSI implementation using a multi-hazard framework to couple different vulnerability indicators and screening rules associated with diverse design criteria and planning regulations. Using a graph-based approach with a simple distributed hydrologic model and mixed-integer linear programing, multi-objective optimization is performed to maximize potential GSI benefits to the most vulnerable areas.
Results from application of the framework in Philadelphia, Pennsylvania, show the spatial synergies and tradeoffs that exist between infiltration structures (e.g., rain gardens, ponds, etc.) and trees as mitigation strategies for flooding and urban heat island. The results highlight the need for more detailed distributed hydrologic modeling to understand the implications of GSI implementation at multiple spatial scales. Using the proposed approach, city and regional organizations can reduce the cost and time associated with identifying suitable areas for GSI implementation and more in-depth design work, as well as improving environmental justice and community buy-in.