A Social Welfare-Based Infrastructure Resilience Assessment Framework: Toward Equitable Resilience for Infrastructure Development Article

Dhakal, S, Zhang, L. (2023). A Social Welfare-Based Infrastructure Resilience Assessment Framework: Toward Equitable Resilience for Infrastructure Development . NATURAL HAZARDS REVIEW, 24(1), 10.1061/(ASCE)NH.1527-6996.0000597

cited authors

  • Dhakal, S; Zhang, L

authors

abstract

  • Resilient infrastructure, which better withstands, adapts, and recovers from disasters, can limit disaster impacts, such as disruptions to infrastructure services and time and efforts needed for recovery. However, in the context of a disaster, the impacts on infrastructure are not evenly distributed across different communities. Thus, we need to account for such disparities (or inequalities) when assessing infrastructure resilience. To address this need, this paper proposes a social-welfare-based infrastructure resilience assessment (SW-Infra-RA) model for quantifying the collective resilience of infrastructure serving multiple communities. This model accounts for (1) disaster inequality - the unequal distributions of disaster impacts on infrastructure across different communities; and (2) disaster vulnerability - the disaster impacts on the infrastructure of communities that suffer from the most severe impacts - both of which have impacts on the collective resilience of infrastructure. A set of hypothetical and real case studies were conducted to illustrate the use of the proposed model in quantitatively assessing infrastructure resilience. This study contributes to the body of knowledge by providing a new infrastructure resilience assessment model that accounts for disaster inequality and vulnerability. The proposed model has the potential to support the development and investment of infrastructure in a more equitable manner; it facilitates equitable resilience in future infrastructure planning and development.

publication date

  • February 1, 2023

published in

Digital Object Identifier (DOI)

volume

  • 24

issue

  • 1