| description abstract | Critical infrastructure systems are interdependent to ensure normal operations for supporting a national economy and social well-being. In the wake of a disaster, such interdependencies may introduce additional vulnerability and cause cascading failures. Therefore, understanding interdependencies and assessing their impact are essential to mitigate such adverse consequences and to enhance disaster resilience in the long term. There have been various models developed to capture dependencies and interdependencies across infrastructure systems. However, problems of inconsistent usage and a lack of technical guidance hinder practical applications of interdependency models. Therefore, this study presents a new classification of interdependency models based on the following implementation methods: dependency tables, interaction rules, and data-driven approaches. For every class of interdependency model, fundamental assumptions and detailed implementation methods are described, with discussion of appropriate application areas, advantages, and limitations. This study also compares different types of models to facilitate analysts in choosing models based on their needs. Due to the intrinsic complexity of dependencies and interdependencies, there are many challenging modeling issues; this study discusses future research directions to address such challenges. | |
