A digital-twin platform for cryospheric disaster warning

Abstract

With increasing glacial hazards due to global climate warming, a promising digital-twin-based platform has been proposed for early warning of cryospheric disasters.

Figure 1.

Conceptualized framework of a digital-twin-based early-warning system for cryospheric disasters. (a) Various hazard types and their scientific data collection in the cryospheric environment. There are five kinds of cryospheric disasters (indicated by blue text) resulting from glacier instability. Such events can cause serious damage to local infrastructures and pose a threat to the water security of downstream communities. Five technical methods (indicated by purple text) can be used to inform the formation, evolution and early warning of cryospheric disasters. The integration of multisource data and their associated inversion algorithms presents challenges in the development of a comprehensive disaster early-warning platform. (b) The digital twin is constructed using virtual reality, supercomputing and cloud sharing technology. (c) Prediction, risk management and early warning at different stages of disaster events. Virtual reality in a digital twin provides an interactive window for requirement uploading and result display. With this window, the digital twin could guide the hazards as well as early warning and mitigation measures for the natural twin.