Abstract
The United Nations Office for Disaster Risk Reduction is developing strategies for stress-testing the resilience of important infrastructure that could be affected by multiple stressors, including climate change. This will help to inform decisions on investment before and after disasters, thus limiting damage to populations, industry or the environment.
The possible effects of severely disruptive events — wildfires, floods and earthquakes, for example — and the requirements for recovery depend on a system’s capacity to recover and transform following such events. Stress-testing with this in mind demands new ways of thinking and new tools, with applications such as levee integrity against floodwaters, transport infrastructure amid a refugee crisis, or hospital bed capacity after a mass casualty event. The financial sector uses such testing to understand the conditions under which institutional finance might buckle.
Stress-testing the resilience of infrastructure gives policymakers a better understanding of system structures and dynamics. It supports the prioritization of sectors and needs in the face of tight budgets. It also provides the option to use network analysis, enabling high-fidelity modelling of systems under real-world conditions.
The possible effects of severely disruptive events — wildfires, floods and earthquakes, for example — and the requirements for recovery depend on a system’s capacity to recover and transform following such events. Stress-testing with this in mind demands new ways of thinking and new tools, with applications such as levee integrity against floodwaters, transport infrastructure amid a refugee crisis, or hospital bed capacity after a mass casualty event. The financial sector uses such testing to understand the conditions under which institutional finance might buckle.
Stress-testing the resilience of infrastructure gives policymakers a better understanding of system structures and dynamics. It supports the prioritization of sectors and needs in the face of tight budgets. It also provides the option to use network analysis, enabling high-fidelity modelling of systems under real-world conditions.
Original language | English |
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Pages (from-to) | 578 |
Number of pages | 1 |
Journal | Nature |
Volume | 603 |
Issue number | 7902 |
DOIs |
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Publication status | Published - 22 Mar 2022 |
Externally published | Yes |