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Infrastructure systems are increasingly exposed to uncertainty, complexity, and rapid change. Natural hazards, accelerating technological development, and growing interdependencies among infrastructure sectors have made infrastructure failures more difficult to anticipate, model, and manage. While individual infrastructure systems are often well understood, their interactions, particularly the cascading failures and nonlinear dynamics that emerge during disruptions, remain poorly captured in practice. Many existing assessment approaches continue to treat infrastructures as largely independent systems, limiting their ability to support decision-making in environments characterized by emergence, surprise, and compounding risk. This paper addresses this gap by identifying, cataloging, and evaluating infrastructure interdependency assessment tools scoped to three sectors: energy, water, and transport. A structured, multi-stage process was used to compile a comprehensive inventory from peer-reviewed and gray literature. Tools were classified and evaluated using a dual framework that combines quantitative scoring of technical dimensions and qualitative assessment of categorical characteristics. The analysis identifies 24 tools within scope, of which only seven explicitly support system-of-systems interdependency assessment for the identified infrastructures. Results reveal an uneven tool landscape: dominance of sector-specific tools, strong emphasis on physical interdependencies, and limited integration of broader interdependency classifications. A fundamental tradeoff emerges between model complexity and practical usability, with no single tool capturing the full breadth of interdependency behavior. By providing a structured comparison and classification of available tools, this study offers guidance on tool selection and highlights key gaps in current modeling approaches, contributing to the advancement of infrastructure resilience assessment in complex, interdependent systems.
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Shamsi et al. (2026) studied this question.
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