Using digital twins to predict flood damage

For the last three years, One Concern has worked with Kumamoto City to increase its resilience to climate-related disasters. To provide the necessary insights to mitigate impacts before a disaster strikes, One Concern built a digital twin to measure overflows from rivers (external flooding), rainfall that exceeds the drainage capacity in urban areas (internal flooding), and floods led by storm surges in coastal areas. The system estimates how the flood water spreads in urban areas and develops different inundation models for river, inland water, and coastal storm surges.

How the platform works

Weather forecast data enables One Concern to estimate where and when flooding is likely to occur. The system also monitors weather information provided periodically by Weathernews, a local weather monitoring organization, and sets thresholds for river water levels, coastal tide levels, and precipitation. If the necessary data is available for large rivers, such as first-class rivers, the system can also predict the river water level for the next 72 hours and display the points where water overflow may occur.

Simulating extreme heavy rain

Flooding from heavy rainfall is a climate-related disaster that occurs with a degree of regularity and can be anticipated days in advance using commonly implemented weather monitoring technology. Instead of relying on limited traditional warning systems to provide intel and scrambling to prepare for incoming devastation, simulating these events with a digital twin can enable flood resilience by providing decision-makers insights to take action before the disaster strikes.