4.6 Article

Evaluating the societal impact of disaster-driven infrastructure disruptions: A water analysis perspective

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ELSEVIER
DOI: 10.1016/j.ijdrr.2020.101988

Keywords

Societal impact; Needs satisfaction analysis; Infrastructure disruption; Infrastructure resilience; Adaptive capacity; Water availability analysis

Funding

  1. National Key Research and Development Program of China [2017YFC1405301]
  2. China Scholarship Council (CSC)

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This study establishes a theoretical framework and proposes an integrated methodology to evaluate the societal impact of disrupted infrastructure in disaster events. The societal impact is based on a water analysis, defined as the percentage of the population in different levels of need satisfaction depending on the amount of water people can obtain. The proposed engineering model combines water supply resilience analysis to estimate water quantity during a disaster event.
Critical infrastructure plays an important role in providing essential products and services to people; however, it is vulnerable to disasters and its disruption can have a severe societal impact. This study establishes a theoretical framework and proposes an integrated methodology to evaluate the societal impact of disrupted infrastructure in disaster events. Here, the societal impact is based on a water analysis and is defined as the percentage of the population in different levels of need satisfaction, which depends on the amount of water that people can obtain. Subsequently, based on water supply resilience analysis, an engineering model is proposed to estimate the water quantity during a disaster event considering the availability of tap water, emergency water, and bottled water. Meanwhile, physical interdependencies among the water supply system, emergency service, commercial facilities, electricity system, and transportation system are incorporated into an availability analysis of the three water sources. Finally, the proposed model is applied to the city of Osaka to validate its applicability and effectiveness. The results demonstrate that the proposed model can provide valuable information to decision-makers about the severity and spatial distribution of the societal impact of infrastructure disruption.

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