An official website of the United States government
Abstract There is a growing understanding that cross‐sector risks faced by critical infrastructure assets in natural disasters require a collaborative foresight from multiple disciplines. However, current contributions to infrastructure interdependency analysis remain centered in discipline‐specific methodologies often constrained by underlying theories and assumptions. This perspective article contributes to ongoing discussions about the uses, challenges, and opportunities provided by interdisciplinary research in critical infrastructure interdependency analysis. In doing so, several modes of integration of computational modeling with contributions from the social sciences and other disciplines are explored to advance knowledge that can improve the infrastructure system resilience under extreme events. Three basic modes of method integration are identified and discussed: (a) integrating engineering models and social science research, (b) engaging communities in participative and collaborative forms of social learning and problem solving using simulation models to facilitate synthesis, exploration, and evaluation of scenarios, and (c) developing interactive simulations where IT systems and humans act as “peers” leveraging the capacity of distributed networked platforms and human‐in‐the‐loop architectures for improving situational awareness, real‐time decision making, and response capabilities in natural disasters. Depending on the conceptualization of the issues under investigation, these broadly defined modes of integration can coalesce to address key issues in promoting interdisciplinary research by outlining potential areas of future inquiry that would be most beneficial to the critical infrastructure protection communities.
more »
« less
Being Prepared to be Unprepared: Meaning Making is Critical for the Resilience of Critical Infrastructure Systems
Infrastructure is essential to provision of public health, safety, and well-being. Yet, even critical infrastructure systems cannot be designed, constructed, and operated to be robust to the myriad of surprising hazards they are likely to be subject to. As such, there has been increasing emphasis in Federal policy on enhancing infrastructure resilience. Nonetheless, existing research on infrastructure systems often overlooks the role of individual decision-making and team dynamics under the conditions of high ambiguity and uncertainty typically associated with surprise. Although evidence suggests that human factors correlating with resilience and adaptive capacity emerge in later stages of psychological development, there is an acute need for new knowledge about the human capacity to comprehend increasing levels of complexity in the context of rapidly evolving technological, ecological, and social stress conditions. Sometimes, it is this developmental capacity for meaning-making that is the difference between adaptive and maladaptive response. Thus, without a better understanding of the human capacity to develop and assign meaning to complex systems, unquestioned misconceptions about the human role may prevail. In this work, we examine the dynamic relationships between human and technological systems from a developmental perspective. We argue that knowledge of resilient human development can improve system resilience by aligning roles and responsibilities with the developmental capacities of individuals and groups responsible for the design, operation, and management of critical infrastructures. Taking a holistic approach that draws on both psychology and resilience engineering literature facilitates construction of an integrated model that lends itself to empirical verification of future research.
more »
« less
- Award ID(s):
- 1760739
- PAR ID:
- 10228185
- Date Published:
- Journal Name:
- Integral review
- Volume:
- 16
- Issue:
- 2
- ISSN:
- 1553-3069
- Page Range / eLocation ID:
- 97-123
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
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.more » « less
-
Abstract Infrastructure resilience plays an important role in mitigating the negative impacts of natural hazards by ensuring the continued accessibility and availability of resources. Increasingly, equity is recognized as essential for infrastructure resilience. Yet, after about a decade of research on equity in infrastructure resilience, what is missing is a systematic overview of the state of the art and a research agenda across different infrastructures and hazards. To address this gap, this paper presents a systematic review of equity literature on infrastructure resilience in relation to natural hazard events. In our systematic review of 99 studies, we followed an 8-dimensional assessment framework that recognizes 4 equity definitions including distributional-demographic, distributional-spatial, procedural, and capacity equity. Significant findings show that (1) the majority of studies found were located in the US, (2) interest in equity in infrastructure resilience has been exponentially rising, (3) most data collection methods used descriptive and open-data, particularly with none of the non-US studies using human mobility data, (4) limited quantitative studies used non-linear analysis such as agent-based modeling and gravity networks, (5) distributional equity is mostly studied through disruptions in power, water, and transportation caused by flooding and tropical cyclones, and (6) other equity aspects, such as procedural equity, remain understudied. We propose that future research directions could quantify the social costs of infrastructure resilience and advocate a better integration of equity into resilience decision-making. This study fills a critical gap in how equity considerations can be integrated into infrastructure resilience against natural hazards, providing a comprehensive overview of the field and developing future research directions to enhance societal outcomes during and after disasters. As such, this paper is meant to inform and inspire researchers, engineers, and community leaders to understand the equity implications of their work and to embed equity at the heart of infrastructure resilience plans.more » « less
-
As critical infrastructure systems consider whether and how to adapt and build resilience to climate variability and change, more research is needed to holistically explore the dynamics of resilience-building changes over time. We begin to fill this gap with a case study of the Rhode Island public wastewater sector. The Rhode Island Department of Environmental Management has invested significant funding, technical assistance, capacity building, and regulatory pressure to help publicly owned wastewater systems build resilience to climate challenges since 2010. To trace, assess, and understand the dynamics of resilience-building efforts over time, we interviewed wastewater utility and municipal personnel using event history calendars (EHCs). EHCs helped respondents recall details of relevant events, including potentially disruptive storms/incidents, and how they responded, including large- and small-scale adaptations, during the study period (2010–2023). We used EHCs to trace resilience and transformation capacities over time, and to analyze and predict movement toward transformational adaptation. We found that factors that best enable movement from incremental to transformational changes include unlocking capacity, or the organizational cultural value of in-depth learning/change, and a suite of contextual supports – new information, forward-looking collaborators, and stable funding sources – which require buy-in across levels of governance. We also found that, with organizational culture considered, experiencing disruption is not predictive of pursuing transformative adaptation. This suggests decision-making strategies for states, local jurisdictions, and utility managers to support climate adaptation and resilience in critical infrastructure, such as eliminating path-dependencies and silos, lowering thresholds for action, and leveraging networks to support moving toward transformation.more » « less
-
Critical infrastructure is the backbone of modern societies. To meet increasing demand under resource-constrained and multihazard conditions, policy-makers are tapping into infrastructure resiliency: its capacity to withstand and recover from disruptions. Thus, resiliency-aware uncertainty quantification is key to identify tipping points, yet it remains computationally inaccessible. This paper maps resiliency measures to well understood time-dependent reliability computations, porting insights and methods from reliability theory to the service of critical infrastructure resiliency and upkeep efforts. For large-scale applications, we use particle integration methods (PIMs)—a family of sequential Monte Carlo methods with wide-ranging applications—and propose their optimal tuning in terms of their variance and number of limit-state function evaluations. We obtain consistent and unbiased probability estimates in applications to dynamical systems, network reliability, and resilience analysis, demonstrating PIMs as practical yet under-appreciated tools. For example, we obtain probability estimates of order 10−14 in networks with over 10,000 random variables.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- The DOI is not currently available.
