Digital Twin for Tsunami Disaster Resilience - Development of TsunamiCast : Real-time Impact-based Tsunami Forecast Facility

Digital Twin for Tsunami Disaster Resilience - Development of TsunamiCast:Real-time Impact-based Tsunami Forecast Facility

Digital twin is generally defined as a digital representation of physical objects in the real world, stored in cyberspace and used to simulate processes and consequences of target phenomena. Recognizing the importance of this concept, we propose Tsunami Digital Twin (TDT) as a new paradigm in tsunami science and engineering aimed at enhancing tsunami disaster resilience. We report recent progress in TDT applications and practical implementations.

Current TDT developments in Japan focus on multi-platform computing capabilities to extend tsunami forecasting technologies to other countries. As part of this effort, we have launched a new project, “TsunamiCast,” which aims to construct both fully cloud-based and on-premises end-to-end tsunami inundation forecasting facility for at-risk coastal communities. The standard TsunamiCast infrastructure integrates two kinds of urgent computing platforms of cloud computing system and on-premises servers having GPU computing capabilities.

The facility first ingests earthquake source information to determine a potential tsunami source model. This process consists of four levels: L1) estimation of earthquake magnitude and hypocenter; L2) centroid moment tensor (CMT) solutions; L3) GNSS-based solutions; and L4) a hybrid procedure that integrates L3 solutions with offshore data assimilation, which is currently under testing. Based on the derived tsunami source, the system performs tsunami propagation and inundation simulations on multiple high-performance computing platforms. These simulations generate time series of tsunami at offshore and coastal tide gauges, and critical points on the land to estimate tsunami travel and arrival times, inundation extents, and maximum flow depth distributions.

The tsunami modeling is conducted using the TUNAMI-N2 model of Tohoku University, which solves the nonlinear shallow-water equations using a finite-difference scheme. Based on the resulting maximum flow depth distributions, the facility conducts GIS-based analyses to estimate exposed populations and assess structural damage by applying tsunami fragility curves. The results are disseminated as map-based products to responders and stakeholders, including national government and regional municipalities, to support emergency response and tsunami disaster management activities. In the other words, TsunamiCast is designed to support two major United Nations global initiatives: Early Warnings for All (EW4ALL) and Tsunami Ready.