Post-Disaster Supply Chain Interdependent Critical Infrastructure System Restoration: A Review of Data Necessary and Available for Modeling

doi:10.5334/dsj-570

Abstract

<p class="p1">The majority of restoration strategies in the wake of large-scale disasters have focused on short-term emergency response solutions. Few consider medium- to long-term restoration strategies to reconnect urban areas to national <em>supply chain interdependent critical infrastructure systems</em> (SCICI). These SCICI promote the effective flow of goods, services, and information vital to the economic vitality of an urban environment. To re-establish the connectivity that has been broken during a disaster between the different SCICI, relationships between these systems must be identified, formulated, and added to a common framework to form a system-level restoration plan. To accomplish this goal, a considerable collection of SCICI data is necessary. The aim of this paper is to review what data are required for model construction, the accessibility of these data, and their integration with each other. While a review of publically available data reveals a dearth of real-time data to assist modeling long-term recovery following an extreme event, a significant amount of static data does exist and these data can be used to model the complex interdependencies needed. For the sake of illustration, a particular SCICI (transportation) is used to highlight the challenges of determining the interdependencies and creating models capable of describing the complexity of an urban environment with the data publically available. Integration of such data as is derived from public domain sources is readily achieved in a geospatial environment, after all geospatial infrastructure data are the most abundant data source and while significant quantities of data can be acquired through public sources, a significant effort is still required to gather, develop, and integrate these data from multiple sources to build a complete model. Therefore, while continued availability of high quality, public information is essential for modeling efforts in academic as well as government communities, a more streamlined approach to a real-time acquisition and integration of these data is essential.

Highlights

Critical infrastructure systems provide the backbone for socioeconomic vitality and security of urban areas
These systems are defined by the US Department of Homeland Security (DHS) as follows: Critical infrastructure are the assets, systems, and networks, whether physical or virtual, so vital to the United States that their incapacitation or destruction would have a debilitating effect on security, national economic security, national public health or safety, or any combination thereof (DHS, 2014)
A supply chain interdependent critical infrastructure system (SCICI) is composed of many systems, including but not limited to: transportation, power, communications, and water, which are interdisciplinary in nature

Summary

Introduction

Critical infrastructure systems provide the backbone for socioeconomic vitality and security of urban areas. A supply chain interdependent critical infrastructure system (SCICI) is composed of many systems, including but not limited to: transportation, power, communications, and water, which are interdisciplinary in nature. These SCICI exhibit complex interdependencies that must be captured to create models that are representative of the true system conditions. Recent disaster management studies use either a qualitative (Carlson & Doyle, 1999; Haimes 2005; Amin & Wollenberg, 2005) or quantitative methodology (MacKenzie et al, 2014; Adams & Stewart, 2014) These efforts fail to capture full system complexity by not combining qualitative and quantitative methodologies and ignoring the interdependencies that lead to emergent behaviors. The mediumto long-term restoration of these systems requires longer time lines and larger financial investments than short-term emergency response, and so a methodology specific for these phases is necessary

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