The National Research Institute for Earth Science and Disaster Resilience (NIED) is working on three tasks: predicting disasters, preventing damage, and realizing speedy reconstruction and recovery efforts in the event of natural disasters such as earthquakes, tsunamis, volcanic eruptions, landslides, torrential rains, blizzards, and ice storms.
In the last three years of the NIED’s fourth mid/long term plan period, which began in 2016, natural disasters have occurred every year, including earthquake disasters such as the 2016 Kumamoto earthquake (M7.3) and the 2018 Iburi, Hokkaido, earthquake (M7.1). Disasters of the rainfall include the heavy rainfall in the northern Kyushu (Fukuoka and Oita) in July 2017, the heavy rain event in southwestern Japan in July 2018, the rainfall in northern Kyushu (Saga) in August 2019, and the heavy rainfall in Kanto and Tohoku in October 2019. There were also other disasters: an avalanche accident on Nasudake in 2017 and a phreatic eruption of Kusatsu-Shiranesan in 2018.
Due to the above-mentioned very frequent occurrence of such natural disasters on the Japanese islands, our institute has conducted several research projects to mitigate the damage from such disasters and to accelerate the recovery from them. As the third NIED special issue in the Journal of Disaster Research, several related research results were presented such as those on seismic disasters (Wakai et al., Nakazawa et al., and Ohsumi et al.), those on climatic disasters (Nakamura, and Ishizawa and Danjo), and those of their integrated researches for disaster risk reduction (Cui et al. and Nakajima et al.).
Although the achievements detailed in these papers are the results of individual research, the NIED hopes that these results as a whole will be fully utilized to promote science and technology for disaster risk reduction and resilience. The NIED hopes that this special issue awakens the readers’ interest in new research and, of course, creates an opportunity for further collaborative works with us.
Introduction to the Special Issue on Cascading Disaster Modelling and Prevention