<![CDATA[Sea level rise (SLR) due to climate change poses an existential threat to coastal areas, especially in archipelagic countries such as Indonesia. An effective policy response requires simulation tools that can represent spatial and temporal dynamics in an integrated manner. This study formulates and tests a spatiotemporal model based on Digital Twin to simulate the impact of SLR on infrastructure, settlements, and coastal ecosystems. This model combines satellite altimetry data (Sentinel-3), bathymetry data, a 2D hydrodynamic model (Delft3D), and CMIP6 climate projections (SSP2-4.5 and SSP5-8.5) within a cloud-based Digital Twin framework. The case study was conducted in urban coastal areas with high subsidence, which are among the areas with the highest rates of land subsidence in the world. The simulation covers KMA scenarios up to 2050, with a spatial resolution of 5 meters and daily temporal resolution. The results show that in the SSP5-8.5 scenario, up to 68% of urban coastal areas with high subsidence will be below the average sea level in 2050 without intervention. This spatiotemporal model achieved a flood prediction accuracy of 91.3% (based on spatial IoU) compared to historical tidal flood data from 2020–2024. In addition, the system allows for the evaluation of the impact of mitigation infrastructure such as the North Coast Sea Wall (NCICD). This study proves that the formulation of spatiotemporal models in Digital Twin provides a critical foundation. Additionally, the system enables the evaluation of the impact of mitigation infrastructure such as the North Coast Sea Wall (NCICD).]]>
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