Abstract

Critical infrastructure systems, including transportation, energy, and water/wastewater, lose their essential functionality when exposed to hazards. The internal complexity of lifeline networks and the cascading interdependency that exists among multiple lifeline networks further augment the impact of external perturbations. To help the networks recover and adapt when adverse events occur, resilience must be built into the system. However, translation of resilience to an operational paradigm remains a challenge because the underlying complexity of the large systems must be deciphered first to translate research into decisions and policies. Moreover, in the context of climate and weather extremes, internal variability dominates in the stakeholder relevant near-term (0–30years). Climate model simulations attempt to capture the inherent variability in climate systems through multiple initial condition ensembles. Hence there is a need to integrate tools for decision-making uncertainty to translate the information available at disparate spatiotemporal scales with varying credibility to stakeholder relevant insights. In addition, the perspective would need to consider a holistic framework that embraces the visualization of potential hydrometeorological threats in addition to critical functions and cascading failures across infrastructure sectors. In this chapter, we discuss the gaps using a unifying lens for climate and weather extreme stressors and stressed systems (infrastructure lifelines). Furthermore, we illustrate a solution framework in the context of the resilience of transportation networks under exacerbated stress from precipitation extremes in changing climate scenarios.

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