Fostering resilience to extreme events within infrastructure systems: Characterizing decision contexts for mitigation and adaptation
Introduction
The resilience of a complex system (defined as its capacity to absorb shocks while maintaining function) has emerged as a fundamental concern for systems managers and researchers (Holling, 1973; Carpenter et al., 2001; Resilience Alliance, 2005). Resilience is also important for those affected by a system failure, such as elected officials, agencies, private organizations, and civil society. Much of the interest in resilience has arisen in work regarding complex social–environmental systems, beginning with predator–prey systems (Walters, 1986), and then spreading widely to a variety of contexts, including regions at risk due to social and environmental pressures (Kasperson et al., 1995), ecosystem renewal (Gunderson et al., 1995), and environmental change from local to global scales (Berkes and Folke, 1998; Berkes et al., 2003), among others. Concepts of resilience are also relevant for engineered systems (Holling, 1996), including infrastructure systems within communities (Chang and Shinozuka, 2004). Resilient infrastructure systems, particularly “lifeline” services such as electric power, water, and health care, are crucial for minimizing the societal impact of extreme events (including earthquakes, storms, floods, or terrorism) when they inevitably occur.2 Infrastructure systems that can withstand external shocks in extreme events may also help avoid system interactions, in which one infrastructure system failure leads to failures in other systems (McDaniels et al., 2007). The Resilience Alliance (www.resalliance.org) views resilience in linked human and natural systems as involving three properties: (i) the capacity to absorb disturbance while remaining within the same functional state or basin of attraction, (ii) the potential for self-organization, and (iii) the capability for learning and adaptation (e.g., Carpenter et al., 2001). The first part of this definition highlights the relevance of resilience for analysis of infrastructure systems, particularly lifeline systems. The latter two properties serve as means for maintaining resilience over time.
The objective of this paper is to explore applied decisions that can help make infrastructure systems more resilient to extreme events. It first builds a conceptual framework for understanding the factors that influence the resilience of infrastructure systems. The paper uses interviews to characterize a framework with diagrams which show sets of decisions that can be pursued to foster two dimensions of system resilience (robustness and rapidity) to extreme events. It then applies this framework to the example of planning for system resilience within individual hospitals in the context of earthquake mitigation efforts. Hence, the paper is not theoretical, but practice-oriented, drawing from evidence regarding a wide array of infrastructure contexts and previous failures to discern common lessons.
Previous research has examined ways of making complex systems more resilient, generally in the context of socio-ecological systems. For example, Holling, 1973, Holling, 1996 and researchers with the Resilience Alliance have stressed the problems that arise when systems managers pursue policies that assume systems have high stability and attempt to foster sustained high outputs, often leading to a reduction in complexity and collapse in output of the system. Berkes and Folke (1998) and Berkes et al. (2003) discuss both management practices and social systems to foster resilience. We proceed here in the spirit of that work, but with a different scale and emphasis. We focus on actions that could be taken (decisions to be made) within a specific infrastructure system, or even a single facility, such as one hospital, to foster resilience to extreme events. Hence our focus is on the kinds of actions that could be taken, and their relationships, to foster infrastructure system resilience within an established administrative framework.
This paper makes four contributions. First, it directly expresses infrastructure system resilience in the context of other works on system resilience. To do so, it provides a basis for understanding robustness and rapidity as two crucial dimensions of infrastructure system resilience. A second contribution is to provide an approach for characterizing ex-ante and ex-post mitigation decisions (before and after extreme events) as contexts in which infrastructure system managers and users have opportunities to increase the resilience of systems through efforts to reduce their vulnerability. A third contribution is to present a means of illustrating relationships among sets of decisions (and their uncertainties) that can be made over time by system managers. The fourth contribution is an application to the hospital sector, through interviews with individual hospital emergency managers, to characterize the relationships among variables and decision opportunities available for improving hospital resilience in extreme events.
The next section of this paper reviews various definitions and characterizations of resilience within the literature of social–environmental systems. It discusses concepts of robustness and rapidity as aspects of resilience within infrastructure systems. Section 3 discusses an analytical approach, which relies on flow diagrams, informed by interviews with system managers. These diagrams characterize the generic decision contexts facing system managers, before and after disasters, to understand the means to help build robustness and rapidity, and thus maintain system function after an extreme event. Section 4 develops a generic version of diagrams that are relevant for structuring mitigation decisions in a wide array of infrastructure contexts. Section 5 applies this framework to a case study of earthquake mitigation in hospitals, while Section 6 concludes by discussing potential uses of the decision diagrams.
Section snippets
Concepts of resilience
The concept of resilience has been developed and explored in fields as varied as psychology, materials science, economics and environmental studies. We focus here on resilience as the ability of specific infrastructure systems (or facilities in these systems) at the urban or regional scales to absorb the shocks of extreme events such as natural disasters.
Some definitions of resilience will be helpful. Holling (1996) distinguished between two fundamentally different perspectives on what
Decision flow diagrams
Influence diagrams are a problem-structuring and model-building approach developed in the decision sciences (Howard and Matheson, 1983). Influence diagrams can have diverse uses, including: serving as the basis for characterizing probabilistic dependence among variables (Shachter, 1986); characterizing “knowledge maps” (an individual's or group's mental representation of an uncertain variable) (Howard, 1988); characterizing different mental models of specific kinds of decisions held by
A generic framework for decisions to foster infrastructure system resilience
Fig. 2 (adapted from Cole, 2006) casts the framework of Fig. 1 directly within the overall cycle of planning, mitigation, event occurrence, adaptation, and recovery for infrastructure disaster management. Here the ex-ante and ex-post decision contexts are embedded within the overall activities of planning and mitigation for extreme events in specific infrastructure systems.
The figure omits many major uncertainties and other influences for visual clarity regarding the overall process. In the
Hospital sector resilience
The kinds of decisions addressed in Fig. 3 can be made more concrete by considering a specific infrastructure facility, or a set of facilities in an infrastructure system. As detailed in Cole (2006), over 20 interviews were conducted with hospital administrators in Taiwan, Los Angeles, California, and Vancouver, British Columbia, to identify the decision opportunities available to enhance hospital infrastructure resilience to extreme events such as earthquakes. While earthquake risk was the
Uses of the decision diagrams
Visual characterization of sets of decisions that influence infrastructure system resilience can be used in several ways. First, they can be used to foster a shared understanding of the systems involved, and in turn, can enhance communication and effectiveness in teams of emergency and operations managers as well as those who actually implement emergency procedures in response to extreme events. The shared understanding and enhanced communication can also make civil society involvement in these
Acknowledgments
The Infrastructure Interdependencies project is supported by the National Science Foundation under Grant number CMS-0332002.
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