In this paper, we propose a digital model to run an evacuation simulation that reflects the road network blockage caused by the landslide and river flooding damage in Marumori-machi, Miyagi Prefecture, which was severely damaged by Typhoon No. 19 in 2019. In particular, we propose an evacuation agent simulation model that can be extended in the future to scenarios related to disaster response decisions, education, and awareness on the part of residents and can reproduce the evacuation agent situation of a real disaster. The method adjusts a set of parameters of vehicles and pedestrian agents to reproduce the evacuation situation. Then, using the parameter set, we perform the agent simulations under different scenarios varying the time of disaster occurrence and evacuation. Finally, we evaluate the changes in the number of people who have completed their evacuation, the number of victims, etc. The results of the scenarios with different disaster occurrence times showed that the final evacuation rate situation improved by at least 1% (about 170 people who completed evacuation) during daylight time compared to nighttime. The relationship between sunset time and the start of evacuation was qualitatively and quantitatively demonstrated to be supported. It was also confirmed that the evacuation situation did not change much with the time of the evacuation announcement. These results show trends limited to the present study’s disasters and scenarios and do not necessarily provide generalized findings for disaster response. However, the results indicate that applying the proposed methodology to a greater number of disasters and scenario conditions could lead to better analysis and optimization of disaster response. Interviews with government disaster management officials in the target areas suggest that confirming the effectiveness of disaster response while visualizing the distribution of disaster risk in the areas from a bird’s eye view, as in this study, could enhance existing response plans. This approach may also present information comprehensibly for staff and residents who did not experience the disaster firsthand, simulating the experience for better understanding.

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