Quantifying systemic vulnerability of interdependent critical infrastructure networks: A case study for volcanic hazards

IF 4.2 1区 地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY
Alana M. Weir , Thomas M. Wilson , Mark S. Bebbington , Craig Campbell-Smart , James H. Williams , Roger Fairclough
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Abstract

Infrastructure networks are vital for the communities and industries that rely on their continued operation. Disasters stress these complex networks and can provoke systemic disruptions that extend far beyond the spatial footprint of hazards. An enduring challenge for assessing infrastructure networks within disaster impact assessment frameworks has been to adequately quantify the high spatial interdependence of these networks, and to consider risk management interventions through time. This is of particular importance for volcanic eruptions, which can produce multiple hazards over highly variable spatiotemporal extents. In this study, we present a methodology for the quantification of systemic vulnerability of infrastructure networks, which can be coupled with physical vulnerability models for the purpose of impact assessment. The two-part methodology first quantifies the haard-agnostic criticality of infrastructural components, inclusive of interdependencies, and then incorporates representative hazard spatial footprints to derive the systemic vulnerability. We demonstrate this methodology using the case study of volcanic eruptions from Taranaki Mounga volcano, Aotearoa New Zealand, where there are many industrial sites of national importance, and a high likelihood of a complex multi-hazard volcanic eruption. We find a considerable increase in the systemic vulnerability of electricity and natural gas network components after incorporating infrastructure interdependencies, and a further increase in the systemic vulnerability of these critical components when cross-referenced with potential volcanic hazard spatial extent. The methodology of this study can be applied to other areas of interest in both its hazard-agnostic or hazard-dependent form, and the systemic vulnerability quantification should be incorporated into impact assessment frameworks.
量化相互依存的关键基础设施网络的系统脆弱性:火山灾害案例研究
基础设施网络对于依赖其持续运行的社区和行业至关重要。灾害会对这些复杂的网络造成压力,并可能引发系统性破坏,远远超出灾害的空间影响范围。在灾害影响评估框架内对基础设施网络进行评估的一个长期挑战是,如何充分量化这些网络在空间上的高度相互依存性,并考虑在时间上进行风险管理干预。这一点对于火山爆发尤为重要,因为火山爆发会在高度可变的时空范围内产生多种危害。在本研究中,我们提出了一种量化基础设施网络系统脆弱性的方法,该方法可与物理脆弱性模型相结合,用于影响评估。该方法由两部分组成,首先量化基础设施各组成部分与灾害无关的关键性,包括相互依存性,然后结合具有代表性的灾害空间足迹得出系统脆弱性。我们使用新西兰奥特亚罗瓦的塔拉纳基-蒙加火山喷发案例研究来演示这种方法,该地区有许多对国家具有重要意义的工业遗址,发生复杂的多种危害的火山喷发的可能性很高。我们发现,在纳入基础设施相互依存关系后,电力和天然气网络组件的系统脆弱性显著增加,而在与潜在火山灾害空间范围相互参照后,这些关键组件的系统脆弱性进一步增加。本研究的方法可应用于其他相关领域,无论是与灾害无关还是依赖于灾害的形式,系统脆弱性量化应纳入影响评估框架。
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来源期刊
International journal of disaster risk reduction
International journal of disaster risk reduction GEOSCIENCES, MULTIDISCIPLINARYMETEOROLOGY-METEOROLOGY & ATMOSPHERIC SCIENCES
CiteScore
8.70
自引率
18.00%
发文量
688
审稿时长
79 days
期刊介绍: The International Journal of Disaster Risk Reduction (IJDRR) is the journal for researchers, policymakers and practitioners across diverse disciplines: earth sciences and their implications; environmental sciences; engineering; urban studies; geography; and the social sciences. IJDRR publishes fundamental and applied research, critical reviews, policy papers and case studies with a particular focus on multi-disciplinary research that aims to reduce the impact of natural, technological, social and intentional disasters. IJDRR stimulates exchange of ideas and knowledge transfer on disaster research, mitigation, adaptation, prevention and risk reduction at all geographical scales: local, national and international. Key topics:- -multifaceted disaster and cascading disasters -the development of disaster risk reduction strategies and techniques -discussion and development of effective warning and educational systems for risk management at all levels -disasters associated with climate change -vulnerability analysis and vulnerability trends -emerging risks -resilience against disasters. The journal particularly encourages papers that approach risk from a multi-disciplinary perspective.
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