Community-Scale Spatial Mapping to Prioritize Green and Grey Infrastructure Locations to Increase Flood Resilience

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ABSTRACT

With increasing investment in infrastructure to address flooding, including green and grey solutions, there are challenges in selecting the type and location of infrastructure. This paper proposes a method to prioritize locations for stormwater infrastructure. Compared to prior work, it considers both green and grey infrastructure and enables detailed spatial analysis of a community. It uses quantitative measures and includes the multiple potential benefits of green versus grey infrastructure. The method is applied to the coastal county of Chatham County, GA, USA. Results show how the methodology is used to select green or grey infrastructure solutions and highlight locations that should be prioritized for infrastructure investment. Analyses accounting for uncertainties in future climate projections and population estimates are also conducted. The method includes local community characteristics, results in clear placement locations, and with decision-maker input, enables solutions to be adapted as stakeholder priorities evolve to increase community flood resilience.

KEYWORDS:

• Flood infrastructure
• decision-making
• infrastructure investment
• GIS
• green infrastructure
• grey infrastructure
• climate change
• community resilience

Data Availability Statement

The data and codes used during this study are available from the corresponding author by reasonable request.

Disclosure Statement

The Coalition for Disaster Resilient Infrastructure (CDRI) reviewed the anonymised abstract of the article, but had no role in the peer review process nor the final editorial decision.

Additional information

Funding

Partial funding support for this work by the National Science Foundation under Grant No. CNS-2133233 is acknowledge; NSFNSF [CNS-2133233]. The Article Publishing Charge (APC) for this article is funded by the Coalition for Disaster Resilient Infrastructure (CDRI).

Notes on contributors

Michelle Reckner

Michelle Reckner is a second-year Ph.D. student at the Georgia Institute of Technology studying Infrastructure Systems Engineering. Reckner received her Bachelor of Mechanical Engineering degree from the University of Delaware with minors in Sustainable Infrastructure, Civil Engineering, and Sustainable Energy Technologies. Her research interests fall into disaster risk management and how infrastructure can support resilient communities.

Iris Tien

Iris Tien is Williams Family Associate Professor in the School of Civil and Environmental Engineering at the Georgia Institute of Technology. Tien received her Ph.D. in Civil Systems Engineering from the University of California, Berkeley. Tien’s research encompasses civil engineering, sensing and data analytics, stochastic processes, probabilistic risk assessment, and decision-making under uncertainty. Her recent work focuses on interdependent infrastructure systems modeling and analysis, and increasing the resilience of communities to a range of disaster events. Her published work has been selected as Editor’s Choice selections in both the ASCE Journal of Infrastructure Systems and the ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems.