## 6 Conclusions  
A DT is a technology that has grown rapidly with the importance of digital transformation and the emergence of Industry 4.0 from the beginning of the 21 st century. Previously, DTs were utilized mainly in manufacturing, aviation, and health care. The use of DTs is expanding dramatically to other large-scale fields, as digital twins of cities, oceans, and the Earth have been constructed. This study serves as a foundation for establishing a well-organized digital twin system of the SIS. The SCHISM model was applied to a 39-day simulation; these 39 days including the typhoon season, when atmospheric conditions were tough and extreme. To make the model even more robust and accurate, more effort was put into the model parameter settings, such as spatially varying filtering parameters calculated from instability factors and spatially varying grid resolution considering bathymetric gradients. Especially after adopting the filtering parameters, the model was able to transition from the Nankai Trough (4900 m depth) to rivers (3 m depth) without requiring grid nesting, despite grid resolution being changed from 9.8 km to 30 m. These efforts allowed us to seamlessly simulate the river-coastal ocean circulations in and around the SIS. The model presented reasonable validation results in terms of elevations, tidal currents, and temperature, and reproduced the storm surge of approximately 2.37 m in Osaka Bay. There was no previous study where a high-resolution model describing all narrow straits in the SIS was established and validated without grid nesting. The model results within one mesh will be utilized as a main data source consisting of a digital twin of the SIS in the future. Although the interaction between reality and the model is an essential requirement for the DT system, methods or concepts for facilitating this interaction and establishing a real-time feedback system are still in the early stages of development even globally, particularly in terms of digital twins of oceans. These interactions have the potential to enhance our understanding and enable more accurate predictions, leading to well-informed decision-making, as digital twins can be used to assess and affect new policies and environmental management practices. However, in this study, we were unable to address this aspect. Our efforts were solely on generating a reliable dataset using the model. The model results were validated in terms of tides, temperatures, and currents. The tidal component outputs showed NRMSE values less than 0.15 and R\({}^{2}\) values larger than 0.87 at forty-two tidal stations in the SIS. We confirmed that tides propagated all the way inside the SIS, though this effect was not well-reproduced in previous literature. Moreover, the model could reproduce the seasonal and fortnight scale temperature trends shown in the observations. The current velocities observed in various layers (5, 10, 20, and 30 m) at mooring stations were used to validate the model results. The NRMSE values ranged from 0.11 to 0.17, and the R\({}^{2}\) values ranged from 0.74 to 0.79. Statistically, the model calculated currents that were approximately 0.05 m/s larger than the observations. However, the slopes of the regression lines were nearly all one, indicating the high reproducibility of the model for velocity variations. The model exhibited high-velocity distributions around narrow straits in the SIS. At the Naruto Strait, famous for its large whirlpools and strong currents, 5 m/s depth-averaged currents were calculated. The model successfully simulated the storm surge caused by Typhoon Jebi in 2018, accurately calculating the observed surge as the typhoon approached Osaka City. The timing of the surge's arrival and its spatial distribution were also accurately reproduced by the model, demonstrating the model's potential for application to other extreme events in the SIS.