Urban resilience is a multifaceted concept including the recovery of the physical infrastructure and various urban activities that depend on that physical infrastructure. It is relatively straightforward to quantify infrastructure resilience by tracking the recovered facilities in time and marking the time that the infrastructure is fully functioning again. However, the physical infrastructure recovery does not necessarily indicate that the urban activities bounce back to the predisaster conditions. The restoration of urban activities depends on the areas that a particular infrastructure serves (e.g., residential, commercial) and the connections with other critical facilities (e.g., health, education). It is important to investigate the infrastructure recovery and “resilience divide” with respect to the enabled services and affected populations in order to achieve all-inclusive resilience. For this purpose, we examined the resilience of different physical elements such as power feeders (i.e., underground or overhead lines), critical facilities (e.g., fire and rescue services, hospitals) and different socio-demographic segments of the population (i.e., different age groups, ethnicities, and income levels) which constitute an urban environment. The analyses were conducted using the power outages experienced after Hurricane Hermine in Tallahassee, as a case study. The findings show that overall resilience performance can be distinct and/or not homogeneous for the resilience of different physical elements, urban services, and population groups.
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Integrating Operational and Organizational Aspects in Interdependent Infrastructure Network Recovery
Managing risk in infrastructure systems implies dealing with interdependent physical networks and their relationships with the natural and societal contexts. Computational tools are often used to support operational decisions aimed at improving resilience, whereas economics‐related tools tend to be used to address broader societal and policy issues in infrastructure management. We propose an optimization‐based framework for infrastructure resilience analysis that incorporates organizational and socioeconomic aspects into operational problems, allowing to understand relationships between decisions at the policy level (e.g., regulation) and the technical level (e.g., optimal infrastructure restoration). We focus on three issues that arise when integrating such levels. First, optimal restoration strategies driven by financial and operational factors evolve differently compared to those driven by socioeconomic and humanitarian factors. Second, regulatory aspects have a significant impact on recovery dynamics (e.g., effective recovery is most challenging in societies with weak institutions and regulation, where individual interests may compromise societal well‐being). And third, the decision space (i.e., available actions) in postdisaster phases is strongly determined by predisaster decisions (e.g., resource allocation). The proposed optimization framework addresses these issues by using: (1) parametric analyses to test the influence of operational and socioeconomic factors on optimization outcomes, (2) regulatory constraints to model and assess the cost and benefit (for a variety of actors) of enforcing specific policy‐related conditions for the recovery process, and (3) sensitivity analyses to capture the effect of predisaster decisions on recovery. We illustrate our methodology with an example regarding the recovery of interdependent water, power, and gas networks in Shelby County, TN (USA), with exposure to natural hazards.
more » « less- Award ID(s):
- 1635717
- NSF-PAR ID:
- 10460607
- Publisher / Repository:
- Wiley-Blackwell
- Date Published:
- Journal Name:
- Risk Analysis
- Volume:
- 39
- Issue:
- 9
- ISSN:
- 0272-4332
- Page Range / eLocation ID:
- p. 1913-1929
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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