A Multi-Hazard Digital Twin Framework for Climate Adaptation Planning of Interdependent Critical Urban Infrastructure

Abstract

Introduction:
Climate change is intensifying compound and cascading hazards, including flooding, extreme heat, and drought, posing systemic risks to interdependent critical urban infrastructure such as transportation, water, and energy networks. Although digital twins (DTs) are increasingly adopted for infrastructure monitoring and smart city management, their application remains largely sector-specific and hazard-isolated. A unified, multi-hazard digital twin framework explicitly designed for climate adaptation planning of interdependent infrastructure systems is still lacking. This study addresses this gap by proposing an integrated framework that moves beyond operational monitoring toward strategic adaptation decision support.

Methods:
This research adopts a two-stage methodology. First, a systematic literature review synthesizes advancements in digital twin architectures, climate risk modeling, and infrastructure interdependency analysis to identify existing research gaps. Second, a novel multi-layered digital twin framework is developed. The proposed architecture integrates (i) multi-hazard climate projection scenarios, (ii) infrastructure interdependency network modeling, (iii) dynamic vulnerability and risk assessment modules, and (iv) an adaptation prioritization engine to support strategic planning. The framework emphasizes interoperability, scalability, and real-time data assimilation.

Results:
The review reveals a critical absence of comprehensive frameworks that simultaneously incorporate multi-hazard modeling and interdependent infrastructure dynamics within a unified digital twin environment. The proposed framework addresses this gap by introducing an integrated architecture that enables cross-sector impact simulation, compound hazard scenario analysis, and risk-informed adaptation prioritization within a single decision-support structure.

Conclusions:
This research advances digital twin applications from operational management toward proactive, multi-hazard climate adaptation planning. The proposed framework establishes a scalable and transferable foundation for future prototype implementation and policy-aligned decision-support systems aimed at strengthening urban infrastructure resilience under deep climate uncertainty.