Addressing the social barriers to green stormwater infrastructure in residential areas from a socio-ecological perspective

J Environ Manage. 2022 Jul 1:313:114987. doi: 10.1016/j.jenvman.2022.114987. Epub 2022 Mar 31.

Abstract

Despite the well-recognized financial limitations, social aspects can also impact the adoption of green stormwater infrastructure (GSI) as it is ingrained in the socio-ecological system we live in. Thus, this work focuses on gaining an understanding of the public's perceptions of GSI by considering cognitive biases that hinder its adoption. This work is composed of two forms of human-subject studies, including an online-based survey and a series of semi-structured interviews. The survey (n = 510) was conducted to gauge public opinions toward GSI, whereas the interviews with representatives of major local regulatory agencies were to learn about the logistics for GSI implementation in Mecklenburg County, NC. The results were interpreted using the theory of planned behavior of rational actors. Statistical results showed a weak interpretation through this theory to explain the survey participants' intention to adopt GSI measures. This could suggest that the incorporation of irrationality, such as cognitive biases, could further enhance the predictability of the theory. At the same time, an inconsistency between the findings from the survey and the interviews was identified: most survey participants showed an overall uniform positive attitude, intention, and behavior regarding GSI practice adoption, whereas the interviewed experts all suggested a wide diversity on such terms. Suggestions were made based on the findings for better policy-making on public engagement for local regulatory agencies. This research aims to help local stormwater management authorities explore shortcomings in current stakeholder engagement plans to gain sustainable support for GSI implementation in urbanized areas.

Keywords: Cognitive biases; Green stormwater infrastructure; Socio-ecological systems; Stormwater management.

MeSH terms

  • Ecosystem*
  • Humans