The impact of climate change and the dynamic nature of environmental conditions underscore the critical need to enhance resilience of systems and process safety considerations. The efficacy of such efforts primarily depends on how resilience is measured. Among the myriad efforts to quantify resilience, composite indicators have emerged as promising tools. However, these indicators typically employ statistical methods to derive weights for aggregation and rely on statistical homogeneity among indicators which can limit their scope and fidelity. In this study, we propose an alternative novel resilience index derived from a system’s structure and the essential conditions for safe operation during and after disruptions. The proposed measure reflects the systems’ ability to resist and respond to failures by addressing possibilities of impact propagation to other infrastructure systems. Moreover, it eliminates the need for weights and allows for compensability among its leading indicators. Using a case study based on the on-site wastewater treatment and disposal systems (OSTDS) in South Florida that faces increasing risks due to rising sea levels, we investigate the validity of the proposed index and perform a comparative analysis with statistically-driven measures. Furthermore, we demonstrate the adaptation of the proposed index for decision making within a generalized optimization framework.
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Measuring Resilience to Sea-Level Rise for Critical Infrastructure Systems: Leveraging Leading Indicators
There has been a growing interest in research on how to define and build indicators of resilience to address challenges associated with sea-level rise. Most of the proposed methods rely on lagging indicators constructed based on the historical performance of an infrastructure sub-system. These indicators are traditionally utilized to build curves that describe the past response of the sub-system to stressors; these curves are then used to predict the future resilience of the sub-system to hypothesized events. However, there is now a growing concern that this approach cannot provide the best insights for adaptive decision-making across the broader context of multiple sub-systems and stakeholders. As an alternative, leading indicators that are built on the structural characteristics that embody system resilience have been gaining in popularity. This structure-based approach can reveal problems and gaps in resilience planning and shed light on the effectiveness of potential adaptation activities. Here, we survey the relevant literature for these leading indicators within the context of sea-level rise and then synthesize the gained insights into a broader examination of the current research challenges. We propose research directions on leveraging leading indicators as effective instruments for incorporating resilience into integrated decision-making on the adaptation of infrastructure systems.
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- Award ID(s):
- 2115275
- PAR ID:
- 10477526
- Publisher / Repository:
- MDPI
- Date Published:
- Journal Name:
- Journal of Marine Science and Engineering
- Volume:
- 11
- Issue:
- 7
- ISSN:
- 2077-1312
- Page Range / eLocation ID:
- 1421
- Subject(s) / Keyword(s):
- leading indicators resilience measures structure-based resilience critical infrastructure adaptation sea-level rise climate adaptation
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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