2:30 PM - 2:45 PM
[U11-04] Digital transformation for mitigating risk of consecutive disasters
★Invited Papers
Keywords:Digital Transformation, Disaster simulation using supercomputers, Data integration
It may be a matter of concern more than real, or I may say such things to frighten people. The probability of an earthquake simultaneously occurring with a typhoon may be very low.
Statistics (Nakai, 2001) said that about 20% of first-class river embankments and 40% of coastal embankments damaged by the 2011 Great East Japan Earthquake and Tsunami left unsafe for six months, which means the end of the typhoon season of that year. The statistics imply a high risk of that kind of consecutive disaster after the Nankai trough earthquake or an earthquake that directly hits the Tokyo area. Civil works should fix embankments damaged by earthquakes with certain periods.
Ministry of Land Infrastructure, Transport and Tourism (MLIT) evaluated the seismic resistance of embankments then MLIT started fixing the vulnerable embankment. This activity may delete the previous concern.
Digitization of the evaluation process shows the current situation of embankment to citizens to make them live without concern. Moreover, citizens change their countermeasure activity against typhoons after checking the information on the vulnerable embankment, which is fundamental digital transformation (DX).
New development of embankments or repairing civil works makes it easier to digitize the information. However, the fact that reports submitted to each authority of rivers have different formats shows difficulty in using the digitized report for a unified database.
The present study explains the difficulty and solution to estimate the damage of posterior hazard after capturing the precedent disaster damage by using the method of Oishi (2021), which includes the automatic transformation of non-BIM data to BIM data using Data Processing Platform (DPP) developed by O-tani et al. (2019). Moreover, Yamanoi et al. (2021) explain that ensemble simulation with uncertain information gives a valuable risk estimation.