Natural hazards pose an increasing threat to society, necessitating the development of effective early warning systems (EWSs). This paper explores their critical role in mitigating the impacts of natural hazards. Its primary objective is to define and categorise the components of EWSs, summarise the components of existing systems, and propose a framework for a comprehensive early warning system. This paper includes a thorough review of the available scientific literature on early warning systems, natural hazards, and their underlying causes. It identifies both primary and secondary causes of selected natural hazards, along with their manifestations. Particular emphasis is placed on the significance of sensors and modern technologies for real-time data collection and processing. Based on this analysis, a framework is proposed that integrates various data sources, technologies, and components to enhance preparedness. The findings highlight the necessity of a holistic approach to early warning systems, one that accounts for different types of disasters and the specific needs of at-risk populations. The proposed framework may serve as a foundation for further development and the implementation of more effective early warning systems.

This study examines the potential of digital twin (DT) technology to strengthen urban security, with a specific focus on flood risk management in smart cities. A DT is understood as a virtual representation of real-world assets and processes, continuously synchronised with data from the physical environment. Building on an analysis of the existing DT literature and maturity assessment, identified operational requirements and the authors’ expertise in crisis management, this study proposes a structured set of DT maturity levels with stage boundary conditions and illustrative measurable indications and designs a maturity-driven data content model for a flood-oriented DT. The framework identifies essential data layers, sensing requirements and integration mechanisms necessary for representing hydrological, infrastructural and environmental conditions at operationally meaningful update frequencies. This study further outlines the conceptual architecture of a flood DT and discusses its potential to support prediction, situational awareness and decision making across crisis management phases. By providing recommendations for DT implementation and highlighting opportunities for future development, this study contributes to ongoing efforts to enhance the resilience and safety of urban areas through advanced digital technologies.